TSP/0000755000176200001440000000000013623676650010736 5ustar liggesusersTSP/NAMESPACE0000644000176200001440000000316713612366100012144 0ustar liggesusersuseDynLib(TSP, .registration = TRUE) importFrom(stats, as.dist, dist) importFrom(utils, read.table, write.table) importFrom(grDevices, gray.colors) importFrom(graphics, image.default, plot, polygon) importFrom(foreach, foreach, "%dopar%") export(TSP, ATSP, ETSP, TOUR, reformulate_ATSP_as_TSP, n_of_cities, insert_dummy, cut_tour, tour_length, solve_TSP, linkern_help, concorde_help, concorde_path, read_TSPLIB, write_TSPLIB, ## as.matrix, as.TSP, as.ATSP, as.ETSP, as.TOUR ) ## TSP/ATSP/ETSP S3method(print, TSP) S3method(n_of_cities, TSP) S3method(labels, TSP) S3method(image, TSP) S3method(print, ATSP) S3method(n_of_cities, ATSP) S3method(labels, ATSP) S3method(image, ATSP) S3method(print, ETSP) S3method(n_of_cities, ETSP) S3method(labels, ETSP) S3method(image, ETSP) S3method(plot, ETSP) S3method(tour_length, TOUR) S3method(tour_length, TSP) S3method(tour_length, ATSP) S3method(tour_length, ETSP) S3method(insert_dummy, TSP) S3method(insert_dummy, ATSP) S3method(insert_dummy, ETSP) S3method(write_TSPLIB, TSP) S3method(write_TSPLIB, ATSP) S3method(write_TSPLIB, ETSP) S3method(solve_TSP, TSP) S3method(solve_TSP, ATSP) S3method(solve_TSP, ETSP) ## coercions S3method(as.TSP, dist) S3method(as.TSP, matrix) S3method(as.dist, TSP) S3method(as.ATSP, dist) S3method(as.ATSP, matrix) S3method(as.matrix, ATSP) S3method(as.ETSP, data.frame) S3method(as.ETSP, matrix) S3method(as.matrix, ETSP) S3method(as.TSP, ETSP) ## TOUR S3method(print, TOUR) S3method(cut_tour, TOUR) S3method(as.TOUR, integer) TSP/README.md0000644000176200001440000000417113271620736012211 0ustar liggesusers# TSP - Traveling Salesperson Problem - R package [![CRAN version](http://www.r-pkg.org/badges/version/TSP)](https://cran.r-project.org/package=TSP) [![CRAN RStudio mirror downloads](http://cranlogs.r-pkg.org/badges/TSP)](https://cran.r-project.org/package=TSP) [![Travis-CI Build Status](https://travis-ci.org/mhahsler/TSP.svg?branch=master)](https://travis-ci.org/mhahsler/TSP) [![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/mhahsler/TSP?branch=master&svg=true)](https://ci.appveyor.com/project/mhahsler/TSP) This package provides the basic infrastructure and some algorithms for the traveling salesman problems (symmetric, asymmetric and Euclidean TSPs). The package provides some simple algorithms and an interface to the Concorde TSP solver and its implementation of the Chained-Lin-Kernighan heuristic. ## Installation __Stable CRAN version:__ install from within R with ```R install.packages("TSP") ``` __Current development version:__ Download package from [AppVeyor](https://ci.appveyor.com/project/mhahsler/TSP/build/artifacts) or install from GitHub (needs devtools). ```R library("devtools") install_github("mhahsler/TSP") ``` ## Usage Load a data set with 312 cities (USA and Canada) and create a TSP object. ```R R> library("TSP") R> data("USCA312") R> tsp <- TSP(USCA312) R> tsp ``` ``` object of class 'TSP' 312 cities (distance 'euclidean') ``` Find a tour using the default heuristic. ```R tour <- solve_TSP(tsp) tour ``` ``` object of class 'TOUR' result of method 'arbitrary_insertion+two_opt' for 312 cities tour length: 40621 ``` An online example application of TSP can be found on [shinyapps](https://shrinidhee.shinyapps.io/SimpleTSP). ## References * Michael Hahsler and Kurt Hornik, [TSP - Infrastructure for the Traveling Salesperson Problem,](http://dx.doi.org/10.18637/jss.v023.i02) _Journal of Statistical Software,_ 22(2), 2007. * [TSP package vignette](https://cran.r-project.org/package=TSP/vignettes/TSP.pdf) with complete examples. * [Reference manual](https://cran.r-project.org/package=TSP/TSP.pdf) * [Concorde TSP solver home page](http://www.math.uwaterloo.ca/tsp/concorde/) TSP/data/0000755000176200001440000000000013623555031011634 5ustar liggesusersTSP/data/USCA312.rda0000644000176200001440000022604412606077054013321 0ustar liggesusers7zXZi"6!XS])TW"nRʟXS#&'ƯNP7ϡBDxo"ZZk_^Cl'תᙧ38_efTaWFon됤1>C}CqR=/x AcGy)4myNc5G_fS B-/'>(f(=Q4uR5ɪ6B.#HAr!CZxCTQ`IsdESaX7¡wuf%Ί4uĕqd QDId!w+n/߰-heBc̕3օ:-U@r "l6{(Ey_mTizu B%ew24,ڗJ {"*'c5E(vzD:1V$:D*knnxz7ҟ(3Dd%+ILѯOd"ݝW xh}dcXc*$"CI2,Ujث- ih"-rDP)8)X7$o:6-Ge }?q_ni|A P’j ;ۃM̙&tX Y5$lD/H6#4xpXæWi6NFMk|c  חlr}Nh7ȘZ;W0?|h1;(%o+q6`B&uyO*bmN^O53o_D[ h'+t%*Nc`ypyӯUS"77K'o2Q`(d<5J+_Q7do]EIXW#-q1BrbR.dk-y v]ptp$@P9Xd7@cLnh̡IUܺ=l|"jW ^on@jJһ_Bg46'*ɵ ]BeK;[ƽRBcV*#G%#1hc]O4GV9Y$/elqƪɾKQl28WUUV;uNا] rK%43]&7x(B{'Ib%BnէX7{YeY2u#یV}ZdKN5a"ݕ+h)逗"5|MwUs0\^B(CYߧ531^ym|Y őWJ#!ScLM b]c~u\[sLy&w8V~#b Ym[OY`#!DN=>☃݃U!! |; @ǰ޹e 3mO߱%›uDSG'OӨ&(<epDX=1`N:\ ga]!]1ro*RYSJJj:l)0H[S@ hǦ^l)$gb s9ێ@v &ƟRub|T\dώUcR A42Z@=@5';ܘ;Y-Ο^_'I&*l/ g Zf"Ie9[}Ro ÇmV/Z(e1r P~gSqT(f+7d}azc,=^J/͝z-Q&cѲzOhť;=D֙&f'M?IKPWl5z܉R!/9A QG'6 Џg+ꢰĔDQ PO6WM398!<'@S}+0%'w8CC#:*H oHsy2";2!kG?+N-]pl1&7"Tbl-J&X5i32Б :[%^,M >|tU[6 JŢHs@6O^qLCYEL#*=?ʪ 2༐'8nMѸǬǬO`+E @(ikz$tir˱yX)}> aֱɋO7W2VA JZ&(*=i~Q+RPkM] @]qS^~4`~M̆ϳ H|諝n-oJbL1Dl>^gtl]O5qT2D~odiQ'W-<&YY~w3X-P*^mgnfdB/8$-΀ץW`HBIeCb>'xB>ps4Y9H }CP[CV*Ro[v2ze둎 һPHu}Ân%Hxq|2yk. a{)6 ȣU. ;y z#TQzLভ fs I@ICSߚY,Ǒb|?P1R 6jp,Դ*l;upd' Ԅ5 AM ݪQY86Z9L^t(j:ڛ[Qdl Ma4R=vϿTai|)b;-O@C?> 8kwݐW:2jG\ ,yH 2GR;qYdV tM*-fAsiu0·?f';lS`oCk.x<AP.L%X,O ngߴTEy0,1>;l*\|$ D un"gDk$NzA< '\Pvs0ɁEpIk ϸ+$EtE=p:hrٜH/n\I_#ã @3 s?h{\wf:휷b~bhndo,ࣆ5kK3ΠT5H 5ɕS@YǦ~ۃ؛Bc~ԑ0TOb3AtF:B2#WUyG-Nj78xDfMؐfs$Chuc ,Ϫُcê e4y3a>_Hv0xBS!h P 1tKU'`)]͓mȵж!Oi˵~җH&C_O+"VhXp-ڰِF dMHJ  itZ.J9p;_^^}һĪָy0xYޠjB_g>ٛ}#ڝ-(cxk)uF^w_78VuSecp*Zm G[96PL"6 ]+MusH0C2==njVPfH^+CNufCedy`lV {󂪘@6r_ŵaoUxI C!@'%7,}W`}#Q!t\[n-gS#+xf`bJz3nwyP ӟkX6ٺƪD/ȜynHGeE쌶}WxvUW6l 6>"k IX,.r ߙK@kbO0c%vD 9?uчy-c-pM&1DBٸwH⼾0qiNR͞5֛C5.(#DNʛrqgS&T>/D4 A~]fT_? 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A dummy city has the same, constant distance (0) to all other cities and is infinitely far from other dummy cities. A dummy city can be used to transform a shortest Hamiltonian path problem (i.e., finding an optimal linear order) into a shortest Hamiltonian cycle problem which can be solved by a TSP solvers (Garfinkel 1985). Several dummy cities can be used together with a TSP solvers to perform rearrangement clustering (Climer and Zhang 2006). } \usage{ insert_dummy(x, n = 1, const = 0, inf = Inf, label = "dummy") } \arguments{ \item{x}{an object of class \code{TSP} or \code{ATSP}.} \item{n}{number of dummy cities.} \item{const}{distance of the dummy cities to all other cities.} \item{inf}{distance between dummy cities.} \item{label}{ labels for the dummy cities. If only one label is given, it is reused for all dummy cities.} } \details{ The dummy cities are inserted after the other cities in \code{x}. A \code{const} of 0 is guaranteed to work if the TSP finds the optimal solution. For heuristics returning suboptimal solutions, a higher \code{const} (e.g., \code{2 * max\{x\}}) might provide better results. } \seealso{ \code{\link{TSP}}, \code{\link{ATSP}} } \author{Michael Hahsler} \references{ Sharlee Climer, Weixiong Zhang (2006): Rearrangement Clustering: Pitfalls, Remedies, and Applications, \emph{Journal of Machine Learning Research} \bold{7}(Jun), pp. 919--943. R.S. Garfinkel (1985): Motivation and modelling (chapter 2). In: E. L. Lawler, J. K. Lenstra, A.H.G. Rinnooy Kan, D. B. Shmoys (eds.) The traveling salesman problem - A guided tour of combinatorial optimization, Wiley \& Sons. } \examples{ ## Example 1: Find a short Hamiltonian path set.seed(1000) x <- data.frame(x = runif(20), y = runif(20), row.names = LETTERS[1:20]) tsp <- TSP(dist(x)) ## add a dummy city to cut the tour into a path tsp <- insert_dummy(tsp, label = "cut") tour <- solve_TSP(tsp) tour plot(x) lines(x[cut_tour(tour, cut = "cut"),]) ## Example 2: Rearrangement clustering of the iris dataset set.seed(1000) data("iris") tsp <- TSP(dist(iris[-5])) ## insert 2 dummy cities to creates 2 clusters tsp_dummy <- insert_dummy(tsp, n = 3, label = "boundary") ## get a solution for the TSP tour <- solve_TSP(tsp_dummy) ## plot the reordered distance matrix with the dummy cities as lines separating ## the clusters image(tsp_dummy, tour) abline(h = which(labels(tour)=="boundary"), col = "red") abline(v = which(labels(tour)=="boundary"), col = "red") ## plot the original data with paths connecting the points in each cluster plot(iris[,c(2,3)], col = iris[,5]) paths <- cut_tour(tour, cut = "boundary") for(p in paths) lines(iris[p, c(2,3)]) ## Note: The clustering is not perfect! } \keyword{manip} TSP/man/reformulate_ATSP_as_TSP.Rd0000644000176200001440000000464112606077054016363 0ustar liggesusers\name{reformulate_ATSP_as_TSP} \alias{reformulate_ATSP_as_TSP} \title{Reformulate a ATSP as a symmetric TSP} \description{ A ATSP can be formulated as a symmetric TSP by doubling the number of cities (Jonker and Volgenant 1983). The solution of the TSP also represents the solution of the original ATSP. } \usage{ reformulate_ATSP_as_TSP(x, infeasible = Inf, cheap = -Inf) } \arguments{ \item{x}{an ATSP.} \item{infeasible}{value for infeasible connections.} \item{cheap}{value for distance between a city and its corresponding dummy city.} } \details{ To reformulate the ATSP as a TSP, for each city a dummy city (e.g, for 'New York' a dummy city 'New York*') is added. Between each city and its corresponding dummy city a negative or very small distance with value \code{cheap} is used. This makes sure that each cities always occurs in the solution together with its dummy city. The original distances are used between the cities and the dummy cities, where each city is responsible for the distance going to the city and the dummy city is responsible for the distance coming from the city. The distances between all cities and the distances between all dummy cities are set to \code{infeasible}, a very large value which makes the infeasible. %The result is a distance matrix for the TSP of the following form: % %\eqn{\begin{pmatrix}\infty & D'^T \\ D' & \infty \end{pmatrix},}{} % %where \eqn{D'} is the original distance matrix with %the diagonal replaced by the value for the \code{cheap_link}. } \value{ a TSP object. } \references{ Jonker, R. and Volgenant, T. (1983): Transforming asymmetric into symmetric traveling salesman problems, \emph{Operations Research Letters, 2, 161--163.} } \seealso{ \code{\link{ATSP}}, \code{\link{TSP}}. } \author{Michael Hahsler} \examples{ data("USCA50") ## set the distances towards Austin to zero which makes it a ATSP austin <- which(labels(USCA50) == "Austin, TX") atsp <- as.ATSP(USCA50) atsp[, austin] <- 0 ## reformulate as a TSP tsp <- reformulate_ATSP_as_TSP(atsp) labels(tsp) ## create tour (now you could use Concorde or LK) tour_atsp <- solve_TSP(tsp, method="nn") head(labels(tour_atsp), n = 10) tour_atsp ## Note that the tour has a lenght of -Inf since the reformulation created ## some -Inf distances ## filter out the dummy cities (we specify tsp so the tour lenght is ## recalculated) tour <- TOUR(tour_atsp[tour_atsp <= n_of_cities(atsp)], tsp = atsp) tour } \keyword{optimize} TSP/man/ETSP.Rd0000644000176200001440000000413012606077054012542 0ustar liggesusers\name{ETSP} \alias{ETSP} \alias{as.ETSP} \alias{as.ETSP.matrix} \alias{as.ETSP.data.frame} \alias{n_of_cities.ETSP} \alias{print.ETSP} \alias{labels.ETSP} \alias{image.ETSP} \alias{plot.ETSP} \title{Class ETSP -- Euclidean traveling salesperson problem} \description{ Constructor to create an instance of a Euclidean traveling salesperson problem (TSP) represented by city coordinates and some auxiliary methods. } \usage{ ## constructor ETSP(x, labels = NULL) ## coercion as.ETSP(x) ## methods \method{n_of_cities}{ETSP}(x) \method{image}{ETSP}(x, order, col = gray.colors(64), \ldots) \method{plot}{ETSP}(x, y = NULL, tour = NULL, tour_lty = 2, tour_col = 1, \ldots) \method{labels}{ETSP}(object, \ldots) \method{print}{ETSP}(x, \ldots) } \arguments{ \item{x, object}{ an object (data.frame or matrix) to be converted into a \code{ETSP} or, for the methods, an object of class \code{ETSP}.} \item{labels}{optional city labels. If not given, labels are taken from \code{x}.} \item{col}{ color scheme for image. } \item{order}{ order of cities for the image as an integer vector or an object of class \code{TOUR}.} \item{tour, y}{ a tour to be visualized.} \item{tour_lty, tour_col}{ line type and color for tour. } \item{\ldots}{ further arguments are passed on.} } \details{ Objects of class \code{ETSP} are internally represented as a \code{matrix} objects (use \code{as.matrix()} to get the \code{matrix} object). } \value{ \code{ETSP()} returns \code{x} as an object of class \code{ETSP}. \code{n_of_cities()} returns the number of cities in \code{x}. \code{labels()} returns a vector with the names of the cities in \code{x}. } \seealso{ \code{\link{TOUR}}, \code{\link{insert_dummy}}, \code{\link{tour_length}}, \code{\link{solve_TSP}}. } \author{Michael Hahsler} \examples{ x <- data.frame(x = runif(20), y = runif(20), row.names = LETTERS[1:20]) ## create a TSP etsp <- ETSP(x) etsp ## use some methods n_of_cities(etsp) labels(etsp) ## plot ETSP and solution tour <- solve_TSP(etsp) tour plot(etsp, tour, tour_col = "red") } \keyword{classes}% at least one, from doc/KEYWORDS TSP/man/Concorde.Rd0000644000176200001440000000701713612366100013521 0ustar liggesusers\name{Concorde} \alias{Concorde} \alias{concorde} \alias{concorde_path} \alias{concorde_help} \alias{linkern_help} \title{Using the Concorde TSP Solver} \description{ The Concorde TSP Solver package contains several solvers. Currently, interfaces to the Concorde solver (Applegate et al. 2001), one of the most advanced and fastest TSP solvers using branch-and-cut, and the Chained Lin-Kernighan (Applegate et al. 2003) implementation are provided in \pkg{TSP}. Concorde can solve TSPs and ETSPs directly. ATSPs are reformulated as larger TSP's and then solved. The Concorde TSP Solver package is freely available for academic research and has to be obtained separately from the Concorde web site (see details). } \usage{ ## set path for executables concorde_path(path) ## obtain a list of command line options for the solvers concorde_help() linkern_help() } \arguments{ \item{path}{ a character string with the path to the directory where the executables are installed. } } \details{ The code of the Concorde TSP package is not included in this package and has to be obtained separately from the Concorde web site (see references). Either download the precompiled executables and place them in a suitable directory and make them executable, or you can get the source code and compile it on your own. \pkg{TSP} needs to know where the executables are. There are two options: (1) use \code{concorde_path()} to set the path to the directory containing the executables for concorde and linkern, or (2) make sure that the executables are in the search path stored in the \code{PATH} environment variable (see \code{link{Sys.setenv}}). \code{\link{solve_TSP}} uses \code{\link{write_TSPLIB}} to write the TSP for Concorde and tries to find the appropriate \code{precision} value (digits after the decimal point) to convert the provided distances into the needed integer value range. The \code{precision} value can also be specified in \code{control} in \code{\link{solve_TSP}} with method Concorde. Warning messages will alert the user if the conversion to integer values results into rounding errors that are worse then what is specified in the \code{precision} control parameter. To get a list of all available command line options which can be used via the \code{clo} option for \code{solve_TSP} use \code{concorde_help()} and \code{linkern_help()}. Several options (\option{-x}, \option{-o}, \option{-N}, \option{-Q}) are not available via \code{solve_TSP} since they are used by the interface. } \seealso{ \code{\link{solve_TSP}}, \code{\link{write_TSPLIB}} } \author{Michael Hahsler} \references{ Concorde home page, \url{http://www.math.uwaterloo.ca/tsp/concorde/} Concorde download page, \url{http://www.math.uwaterloo.ca/tsp/concorde/downloads/downloads.htm} David Appletgate, Robert Bixby, Vasek Chvatal, William Cook (2001): TSP cuts which do not conform to the template paradigm, Computational Combinatorial Optimization, M. Junger and D. Naddef (editors), Springer-Verlag. David Applegate and William Cook and Andre Rohe (2003): Chained Lin-Kernighan for Large Traveling Salesman Problems, \emph{INFORMS Journal on Computing}, \bold{15}, 82--92. } \examples{ \dontrun{ ## see if Concorde is correctly installed concorde_path() ## set path to the Concorde executible if it is not in the search PATH ## Example: ## concorde_path("~/concorde/") concorde_help() data("USCA312") ## run concorde only with fast cuts (-V) solve_TSP(USCA312, method = "concorde", control = list(clo = "-V")) } } \keyword{documentation}% at least one, from doc/KEYWORDS TSP/man/TSP.Rd0000644000176200001440000000362213373425054012441 0ustar liggesusers\name{TSP} \alias{TSP} \alias{as.TSP} \alias{as.TSP.matrix} \alias{as.TSP.dist} \alias{n_of_cities} \alias{n_of_cities.TSP} \alias{print.TSP} \alias{labels.TSP} \alias{image.TSP} \title{Class TSP -- Symmetric traveling salesperson problem} \description{ Constructor to create an instance of a symmetric traveling salesperson problem (TSP) and some auxiliary methods. } \usage{ ## constructor TSP(x, labels = NULL, method = NULL) ## coercion as.TSP(x) ## methods \method{n_of_cities}{TSP}(x) \method{image}{TSP}(x, order, col = gray.colors(64), \ldots) \method{labels}{TSP}(object, \ldots) \method{print}{TSP}(x, \ldots) } \arguments{ \item{x, object}{ an object (currently \code{dist} or a symmetric matrix) to be converted into a \code{TSP} or, for the methods, an object of class \code{TSP}.} \item{labels}{optional city labels. If not given, labels are taken from \code{x}.} \item{method}{optional name of the distance metric. If \code{x} is a \code{dist} object, then the method is taken from that object. } \item{col}{ color scheme for image. } \item{order}{ order of cities for the image as an integer vector or an object of class \code{TOUR}.} \item{\ldots}{ further arguments are passed on.} } \details{ Objects of class \code{TSP} are internally represented as \code{dist} objects (use \code{as.dist()} to get the \code{dist} object). } \value{ \code{TSP()} returns \code{x} as an object of class \code{TSP}. \code{n_of_cities()} returns the number of cities in \code{x}. \code{labels()} returns a vector with the names of the cities in \code{x}. } \seealso{ \code{\link{TOUR}}, \code{\link{insert_dummy}}, \code{\link{tour_length}}, \code{\link{solve_TSP}}. } \author{Michael Hahsler} \examples{ data("iris") d <- dist(iris[-5]) ## create a TSP tsp <- TSP(d) tsp ## use some methods n_of_cities(tsp) labels(tsp) image(tsp) } \keyword{classes}% at least one, from doc/KEYWORDS TSP/man/USCA312.Rd0000644000176200001440000000375313623555177012771 0ustar liggesusers\name{USCA} \alias{USCA312} \alias{USCA312_GPS} \alias{USCA50} \docType{data} \title{USCA312/USCA50 -- 312/50 cities in the US and Canada} \description{ The \code{USCA312} dataset contains the distances between 312 cities in the US and Canada as an object of class \code{TSP}. \code{USCA50} is a subset of \code{USCA312} containing only the first 50 cities. The \code{USCA312_GPS} dataset contains the location (long/lat) of the 312 cities. } \usage{ data("USCA312") data("USCA312_GPS") data("USCA50") } \format{ \code{USCA312} and \code{USCA50} are objects of class \code{TSP}. \code{USCA312_GPS} is a data.frame with city name, long and lat. } \note{ We want to thank Roger Bivand for his help with plotting the map. } \source{ John Burkardt, CITIES -- City Distance Datasets, Florida State University, Department of Scientific Computing } \author{Michael Hahsler} \examples{ data("USCA312") ## calculate a tour tour <- solve_TSP(USCA312) tour data("USCA312_GPS") head(USCA312_GPS) # The following examples requite the suggested package sp, maps, and maptools. # We run the example only if the packages are installed. if(require(sp) && require(maps) && require(maptools)) { library("sp") library("maps") library("maptools") data("USCA312_GPS") # create spatial coordinates and a basemap using WGS84 projection. USCA312_coords <- SpatialPointsDataFrame(cbind(USCA312_GPS$long, USCA312_GPS$lat), proj4string=CRS("+proj=longlat +datum=WGS84"), data = USCA312_GPS) USCA312_basemap <- map2SpatialLines(map("world", xlim=c(-166,-47), ylim=c(15,83), plot=FALSE), proj4string=CRS("+proj=longlat +datum=WGS84")) ## plot map plot(as(USCA312_coords, "Spatial"), axes=TRUE) plot(USCA312_basemap, add=TRUE, col = "gray") ## plot tour and add cities tour_line <- SpatialLines(list(Lines(list( Line(USCA312_coords[c(tour, tour[1]),])), ID="1"))) plot(tour_line, add=TRUE, col = "red") points(USCA312_coords, pch=3, cex=0.4, col="black") } } \keyword{datasets} TSP/man/solve_TSP.Rd0000644000176200001440000002617213514032543013650 0ustar liggesusers\name{solve_TSP} \alias{solve_TSP} \alias{solve_TSP.TSP} \alias{solve_TSP.ATSP} \alias{solve_TSP.ETSP} \title{TSP solver interface} \description{ Common interface to all TSP solvers in this package. } \usage{ solve_TSP(x, method = NULL, control = NULL, ...) \S3method{solve_TSP}{TSP}(x, method = NULL, control = NULL, ...) \S3method{solve_TSP}{ETSP}(x, method = NULL, control = NULL, ...) \S3method{solve_TSP}{ATSP}(x, method = NULL, control = NULL, as_TSP = FALSE, ...) } \arguments{ \item{x}{ the TSP given as an object of class \code{TSP}, \code{ATSP} or \code{ETSP}.} \item{method}{ method to solve the TSP (default: arbitrary insertion algorithm with two_opt refinement. } \item{control}{ a list of arguments passed on to the TSP solver selected by \code{method}.} \item{as_TSP}{ should the ATSP reformulated as a TSP for the solver?} \item{...}{ additional arguments are added to \code{control}.} } \details{ Treatment of \code{NA}s and infinite values in \code{x}: \code{TSP} and \code{ATSP} contain distances and \code{NA}s are not allowed. \code{Inf} is allowed and can be used to model the missing edges in incomplete graphs (i.e., the distance between the two objects is infinite). Internally, \code{Inf} is replaced by a large value given by \eqn{max(x) + 2 range(x)}. Note that the solution might still place the two objects next to each other (e.g., if \code{x} contains several unconnected subgraphs) which results in a path length of \code{Inf}. All heuristics can be used with the control arguments \code{repetitions} (uses the best from that many repetitions with random starts) and \code{two_opt} (a logical indicating if two_opt refinement should be performed). If several repetitions are done (this includes method \code{"repetitive_nn"}) then \pkg{foreach} is used so they can be performed in parallel on multiple cores/machines. To enable parallel execution an appropriate parallel backend needs to be registered (e.g., load \pkg{doParallel} and register it with \code{registerDoParallel()}). \code{ETSP} are currently solved by first calculating a dissimilarity matrix (a \code{TSP}). Only concorde and linkern can solve the TSP directly on the \code{ETSP}. Some solvers (including Concorde) cannot directly solve \code{ATSP} directly. \code{ATSP} can be reformulated as larger \code{TSP} and solved this way. For convenience, \code{solve_TSP()} has an extra argument \code{as_TSP} which can be set to \code{TRUE} to automatically solve the \code{ATSP} reformulated as a \code{TSP} (see \code{\link{reformulate_ATSP_as_TSP}}). Currently the following methods are available: \describe{ \item{\code{"identity"}, \code{"random"}}{return a tour representing the order in the data (identity order) or a random order.} \item{\code{"nearest_insertion"}, \code{"farthest_insertion"}, \code{"cheapest_insertion"}, \code{"arbitrary_insertion"} }{ Nearest, farthest, cheapest and arbitrary insertion algorithms for a symmetric and asymmetric TSP (Rosenkrantz et al. 1977). The distances between cities are stored in a distance matrix \eqn{D} with elements \eqn{d(i,j)}. All insertion algorithms start with a tour consisting of an arbitrary city and choose in each step a city \eqn{k} not yet on the tour. This city is inserted into the existing tour between two consecutive cities \eqn{i} and \eqn{j}, such that \deqn{d(i,k) + d(k,j) - d(i,j)} is minimized. The algorithms stops when all cities are on the tour. The nearest insertion algorithm chooses city \eqn{k} in each step as the city which is \emph{nearest} to a city on the tour. For farthest insertion, the city \eqn{k} is chosen in each step as the city which is \emph{farthest} to any city on the tour. Cheapest insertion chooses the city \eqn{k} such that the cost of inserting the new city (i.e., the increase in the tour's length) is minimal. Arbitrary insertion chooses the city \eqn{k} randomly from all cities not yet on the tour. Nearest and cheapest insertion tries to build the tour using cities which fit well into the partial tour constructed so far. The idea behind behind farthest insertion is to link cities far away into the tour fist to establish an outline of the whole tour early. Additional control options: \describe{ \item{\code{start}}{index of the first city (default: random city).} } } \item{\code{"nn", "repetitive_nn"}}{ Nearest neighbor and repetitive nearest neighbor algorithms for symmetric and asymmetric TSPs (Rosenkrantz et al. 1977). The algorithm starts with a tour containing a random city. Then the algorithm always adds to the last city on the tour the nearest not yet visited city. The algorithm stops when all cities are on the tour. Repetitive nearest neighbor constructs a nearest neighbor tour for each city as the starting point and returns the shortest tour found. Additional control options: \describe{ \item{\code{start}}{ index of the first city (default: random city). } } } \item{\code{"two_opt"}}{Two edge exchange improvement procedure (Croes 1958). This is a tour refinement procedure which systematically exchanges two edges in the graph represented by the distance matrix till no improvements are possible. Exchanging two edges is equal to reversing part of the tour. The resulting tour is called \emph{2-optimal.} This method can be applied to tours created by other methods or used as its own method. In this case improvement starts with a random tour. Additional control options: \describe{ \item{\code{tour}}{ an existing tour which should be improved. If no tour is given, a random tour is used. } \item{\code{two_opt_repetitions}}{ number of times to try two_opt with a different initial random tour (default: 1). } } } \item{\code{"concorde"}}{Concorde algorithm (Applegate et al. 2001). Concorde is an advanced exact TSP solver for \emph{only symmetric} TSPs based on branch-and-cut. The program is not included in this package and has to be obtained and installed separately (see \code{\link{Concorde}}). Additional control options: \describe{ \item{\code{exe}}{ a character string containing the path to the executable (see \code{Concorde}).} \item{\code{clo}}{ a character string containing command line options for Concorde, e.g., \code{control = list(clo = "-B -v")}. See \code{concorde_help} on how to obtain a complete list of available command line options.} \item{\code{precision}}{ an integer which controls the number of decimal places used for the internal representation of distances in Concorde. The values given in \code{x} are multiplied by \eqn{10^{precision}} before being passed on to Concorde. Note that therefore the results produced by Concorde (especially lower and upper bounds) need to be divided by \eqn{10^{precision}} (i.e., the decimal point has to be shifted \code{precision} placed to the left). The interface to Concorde uses \code{write_TSPLIB} (see there for more information).} } } \item{\code{"linkern"}}{Concorde's Chained Lin-Kernighan heuristic (Applegate et al. 2003). The Lin-Kernighan (Lin and Kernighan 1973) heuristic uses variable \eqn{k} edge exchanges to improve an initial tour. The program is not included in this package and has to be obtained and installed separately (see \code{\link{Concorde}}). Additional control options: see Concorde above. } %\item{\code{"grasp"}}{ % Greedy Randomized Adaptive Search Procedure (L.S. Pitsoulis % and M.G.C. Resende 2001). % % GRASP is a metaheuristic for combinatorial optimization. It is % implemented as a multistart procedure, in which in each iteration a % random route is constructed (construction phase). To find an % optimum the route is improved by a local search algorithm % (implemented as k-opt neighborhood search). This is % repeatedly done until a stopping criterium is reached (i.e., a number of % iterations). % % Additional control options: % \describe{ % \item{\code{start}}{index of the first city (default: random % city).} % \item{\code{iterations}}{an integer containing the number of % iterations after the algorithm stops (default: 100 iterations).} % \item{\code{max_i}}{an integer representing the max. steps to find % a better solution in local search (default: 100 steps).} % \item{\code{k}}{an integer needed to change k edges of the tour in % local search (default: 3 cities).} % } % } } } \value{ An object of class \code{TOUR}. } \seealso{ \code{\link{TOUR}}, \code{\link{TSP}}, \code{\link{ATSP}}, \code{\link{write_TSPLIB}}, \code{\link{Concorde}}. } \author{Michael Hahsler} \references{ David Appletgate, Robert Bixby, Vasek Chvatal, William Cook (2001): TSP cuts which do not conform to the template paradigm, Computational Combinatorial Optimization, M. Junger and D. Naddef (editors), Springer. D. Applegate, W. Cook and A. Rohe (2003): Chained Lin-Kernighan for Large Traveling Salesman Problems. \emph{INFORMS Journal on Computing, 15(1):82--92.} G.A. Croes (1958): A method for solving traveling-salesman problems. \emph{Operations Research, 6(6):791--812.} S. Lin and B. Kernighan (1973): An effective heuristic algorithm for the traveling-salesman problem. \emph{Operations Research, 21(2): 498--516.} %L.S. Pitsoulis and M.G.C. Resende (2001): Greedy randomized adaptive search %procedures. In P.M. Pardalos and M.G.C. Resende, editors, Handbook of Applied %Optimization, pp. 168--181. D.J. Rosenkrantz, R. E. Stearns, and Philip M. Lewis II (1977): An analysis of several heuristics for the traveling salesman problem. \emph{SIAM Journal on Computing, 6(3):563--581.} } \examples{ ## solve a simple Euclidean TSP (using the default method) etsp <- ETSP(data.frame(x = runif(20), y = runif(20))) tour <- solve_TSP(etsp) tour tour_length(tour) plot(etsp, tour) ## compare methods data("USCA50") USCA50 methods <- c("identity", "random", "nearest_insertion", "cheapest_insertion", "farthest_insertion", "arbitrary_insertion", "nn", "repetitive_nn", "two_opt") ## calculate tours tours <- lapply(methods, FUN = function(m) solve_TSP(USCA50, method = m)) names(tours) <- methods ## use the external solver which has to be installed separately \dontrun{ tours$concorde <- solve_TSP(USCA50, method = "concorde") tours$linkern <- solve_TSP(USCA50, method = "linkern") } ## register a parallel backend to perform repetitions in parallel \dontrun{ library(doParallel) registerDoParallel() } ## add some tours using repetition and two_opt refinements tours$'nn+two_opt' <- solve_TSP(USCA50, method="nn", two_opt=TRUE) tours$'nn+rep_10' <- solve_TSP(USCA50, method="nn", rep=10) tours$'nn+two_opt+rep_10' <- solve_TSP(USCA50, method="nn", two_opt=TRUE, rep=10) tours$'arbitrary_insertion+two_opt' <- solve_TSP(USCA50) ## show first tour tours[[1]] ## compare tour lengths opt <- 14497 # obtained by Concorde tour_lengths <- c(sort(sapply(tours, tour_length), decreasing = TRUE), optimal = opt) dotchart(tour_lengths/opt*100-100, xlab = "percent excess over optimum") } \keyword{optimize}% at least one, from doc/KEYWORDS TSP/man/tour_length.Rd0000644000176200001440000000235512606077054014330 0ustar liggesusers\name{tour_length} \alias{tour_length} \alias{tour_length.TOUR} \alias{tour_length.TSP} \alias{tour_length.ATSP} \alias{tour_length.ETSP} \title{Calculate the length of a tour} \description{ Calculate the length of a tour given a TSP and an order. } \usage{ tour_length(x, ...) \method{tour_length}{TOUR}(x, tsp = NULL, \ldots) } \arguments{ \item{x}{an object of class \code{TOUR}.} \item{tsp}{a TSP object of class \code{TSP}, \code{ATSP} or \code{ETSP}.} \item{\ldots}{further arguments are currently unused.} } \details{ If no \code{tsp} is given, then the tour length stored in \code{x} as attribute \code{"tour_length"} is returned. If \code{tsp} is given then the tour length is recalculated. If a distance in the tour is infinite, the result is also infinite. If the tour contains positive and negative infinite distances then the method returns \code{NA}. } \seealso{ \code{\link{TOUR}}, \code{\link{TSP}}, \code{\link{ATSP}} and \code{\link{ETSP}}. } \author{Michael Hahsler} \examples{ data("USCA50") ## original order tour_length(solve_TSP(USCA50, method="identity")) ## length of a manually created (random) tour tour <- TOUR(sample(seq(n_of_cities(USCA50)))) tour tour_length(tour) tour_length(tour, USCA50) } \keyword{optimize} TSP/man/TOUR.Rd0000644000176200001440000000365412606077054012572 0ustar liggesusers\name{TOUR} \alias{TOUR} \alias{print.TOUR} \alias{as.TOUR} \alias{as.TOUR.integer} \title{Class TOUR -- Solution to a traveling salesperson problem} \description{ Class to store the solution of a TSP. Objects of this class are returned by TSP solvers in this package. Essentially, an object of class \code{TOUR} is a permutation vector containing the order of cities to visit. } \usage{ ## conctructor TOUR(x, method=NA, tsp=NULL) ## coercion as.TOUR(object) ## methods \method{print}{TOUR}(x, \ldots) } \arguments{ \item{x}{ an integer permutation vector or, for the methods an object of class \code{TOUR}}. \item{object}{ data (an integer vector) which can be coerced to \code{TOUR}.}. \item{method}{ character string; method used to create the tour.} \item{tsp}{ \code{TSP} object the tour applies to. If available then the tour will include the tour length. Also the labes of the cities will be available in the tour (otherwise the labels of \code{x} are used).} \item{\ldots}{ further arguments are passed on.} } \details{ Since an object of class \code{TOUR} is an integer vector, it can be subsetted as an ordinary vector or coerced to an integer vector using \code{as.integer()}. It also contains the names of the objects as labels. Additionally, \code{TOUR} has the following attributes: \code{"method"}, \code{"tour_length"}. For most functions, e.g., \code{tour_length} or \code{image}, the \code{TSP/ATSP} object used to find the tour is still needed, since the tour does not contain the distance information. } \seealso{ \code{\link{TSP}}, \code{\link{ATSP}}, \code{\link{tour_length}}, \code{\link{image}}. } \author{Michael Hahsler} \examples{ TOUR(1:10) ## calculate a tour data("USCA50") tour <- solve_TSP(USCA50) tour ## get permutation vector as.integer(tour) ## get tour length directly from tour attr(tour, "tour_length") ## show labels labels(tour) } \keyword{classes}% at least one, from doc/KEYWORDS TSP/man/ATSP.Rd0000644000176200001440000000406613373425054012545 0ustar liggesusers\name{ATSP} \alias{ATSP} \alias{as.ATSP} \alias{as.ATSP.dist} \alias{as.ATSP.matrix} \alias{n_of_cities.ATSP} \alias{print.ATSP} \alias{labels.ATSP} \alias{image.ATSP} \alias{as.matrix} \alias{as.matrix.ATSP} \title{Class ATSP -- Asymmetric traveling salesperson problem} \description{ Constructor to create an instance of the asymmetric traveling salesperson problem (ATSP) and some auxiliary methods. } \usage{ ## constructor ATSP(x, labels = NULL, method = NULL) ## coercion as.ATSP(x) ## methods \method{n_of_cities}{ATSP}(x) \method{image}{ATSP}(x, order, col = gray.colors(64), \ldots) \method{labels}{ATSP}(object, \ldots) \method{print}{ATSP}(x, \ldots) } \arguments{ \item{x, object}{ an object (a square matrix) to be converted into an \code{ATSP} or, for the methods, an object of class \code{ATSP}.} \item{labels}{optional city labels. If not given, labels are taken from \code{x}.} \item{method}{optional name of the distance metric.} \item{col}{ color scheme for image. } \item{order}{ order of cities as an integer vector or an object of class \code{TOUR}.} \item{\ldots}{ further arguments are passed on.} } \details{ Objects of class \code{ATSP} are internally represented by a matrix (use \code{as.matrix()} to get just the matrix). ATSPs can be transformed into (larger) symmetric TSPs using \code{reformulate_ATSP_as_TSP()}. } \value{ \code{ATSP()} returns \code{x} as an object of class \code{ATSP}. \code{n_of_cities()} returns the number of cities in \code{x}. \code{labels()} returns a vector with the names of the cities in \code{x}. } \seealso{ \code{\link{TOUR}}, \code{\link{insert_dummy}}, \code{\link{tour_length}}, \code{\link{reformulate_ATSP_as_TSP}}, \code{\link{solve_TSP}}. } \author{Michael Hahsler} \examples{ data <- matrix(runif(10^2), ncol = 10, dimnames = list(1:10, 1:10)) atsp <- ATSP(data) atsp ## use some methods n_of_cities(atsp) labels(atsp) ## calculate a tour tour <- solve_TSP(atsp, method = "nn") tour tour_length(tour) image(atsp, tour) } \keyword{classes}% at least one, from doc/KEYWORDS TSP/man/TSPLIB.Rd0000644000176200001440000000551213612366100012760 0ustar liggesusers\name{TSPLIB} \alias{TSPLIB} \alias{write_TSPLIB} \alias{write_TSPLIB.TSP} \alias{write_TSPLIB.ATSP} \alias{write_TSPLIB.ETSP} \alias{read_TSPLIB} \title{Read and write TSPLIB files} \description{ Reads and writes TSPLIB format files. TSPLIB files can be used by most TSP solvers. Sample instances for the TSP in TSPLIB format are available on the TSPLIB homepage (see references). } \usage{ write_TSPLIB(x, file, precision = 6, inf = NULL, neg_inf = NULL) read_TSPLIB(file, precision = 0) } \arguments{ \item{x}{ an object of class \code{TSP}, \code{ATSP} or \code{ETSP}. \code{NA}s are not allowed.} \item{file}{ file name or a \code{connection}. } \item{precision}{ controls the number of decimal places used to represent distances (see details). If \code{x} already is \code{integer}, this argument is ignored and \code{x} is used as is.} \item{inf}{ replacement value for \code{Inf} (TSPLIB format cannot handle \code{Inf}). If \code{inf} is \code{NULL}, a large value of \eqn{max(x) + 2 range(x)} (ignoring infinite entries) is used. } \item{neg_inf}{ replacement value for \code{-Inf}. If no value is specified, a small value of \eqn{min(x) - 2 range(x)} (ignoring infinite entries) is used. } } \details{ In the TSPLIB format distances are represented by integer values. Therefore, if \code{x} contains \code{double} values (which is normal in R) the values given in \code{x} are multiplied by \eqn{10^{precision}} before coercion to \code{integer}. Note that therefore all results produced by programs using the TSPLIB file as input need to be divided by \eqn{10^{precision}} (i.e., the decimal point has to be shifted \code{precision} placed to the left). Currently only the following \code{EDGE_WEIGHT_TYPE}s are implemented: \code{EXPLICIT}, \code{EUC_2D} and \code{EUC_3D}. } \value{ \code{read_TSPLIB} returns an object of class \code{TSP} or \code{ATSP}. } \author{Michael Hahsler} \references{TSPLIB home page, \url{http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/} } \examples{ ## Drilling problem from TSP drill <- read_TSPLIB(system.file("examples/d493.tsp", package = "TSP")) drill tour <- solve_TSP(drill, method = "nn", two_opt = TRUE) tour plot(drill, tour, cex=.6, col = "red", pch= 3, main = "TSPLIB: d493") ## Write and read data in TSPLIB format x <- data.frame(x=runif(5), y=runif(5)) ## create TSP, ATSP and ETSP (2D) tsp <- TSP(dist(x)) atsp <- ATSP(dist(x)) etsp <- ETSP(x[,1:2]) write_TSPLIB(tsp, file="example.tsp") #file.show("example.tsp") r <- read_TSPLIB("example.tsp") r write_TSPLIB(atsp, file="example.tsp") #file.show("example.tsp") r <- read_TSPLIB("example.tsp") r write_TSPLIB(etsp, file="example.tsp") #file.show("example.tsp") r <- read_TSPLIB("example.tsp") r ## clean up unlink("example.tsp") } \keyword{file}% at least one, from doc/KEYWORDS TSP/man/cut_tour.Rd0000644000176200001440000000222413612366100013624 0ustar liggesusers\name{cut_tour} \alias{cut_tour} \alias{cut_tour.TOUR} \title{Cut a tour to form a path} \description{ Cuts a tour at a specified city to form a path. } \usage{ cut_tour(x, cut, exclude_cut = TRUE) } \arguments{ \item{x}{an object of class \code{TOUR}.} \item{cut}{the index or label of the city/cities to cut the tour.} \item{exclude_cut}{exclude the city where we cut? If \code{FALSE}, the city at the cut is included in the path as the first city.} } \value{ Retuns a named vector with city ids forming the path. If multiple cuts are used then a list with paths is returned. } \seealso{ \code{\link{TOUR}}. } \author{Michael Hahsler} \examples{ data("USCA50") ## find a path starting at Austin, TX tour <- solve_TSP(USCA50) path <- cut_tour(tour, cut = "Austin, TX", exclude_cut = FALSE) path ## cut the tours at two cities tour <- solve_TSP(USCA50) path <- cut_tour(tour, cut = c("Austin, TX", "Cambridge, MA"), exclude_cut = FALSE) path ## cut a tour at the largest gap using a dummy city tsp <- insert_dummy(USCA50, label = "cut") tour <- solve_TSP(tsp) ## cut tour into path at the dummy city path <- cut_tour(tour, "cut") path } \keyword{optimize} TSP/DESCRIPTION0000644000176200001440000000231713623676650012447 0ustar liggesusersPackage: TSP Type: Package Title: Traveling Salesperson Problem (TSP) Version: 1.1-9 Date: 2020-02-20 Authors@R: c( person("Michael", "Hahsler", role = c("aut", "cre", "cph"), email = "mhahsler@lyle.smu.edu"), person("Kurt", "Hornik", role = c("aut", "cph"))) Description: Basic infrastructure and some algorithms for the traveling salesperson problem (also traveling salesman problem; TSP). The package provides some simple algorithms and an interface to the Concorde TSP solver and its implementation of the Chained-Lin-Kernighan heuristic. The code for Concorde itself is not included in the package and has to be obtained separately. Classification/ACM: G.1.6, G.2.1, G.4 URL: https://github.com/mhahsler/TSP BugReports: https://github.com/mhahsler/TSP/issues Depends: R (>= 3.5.0) Imports: graphics, foreach, utils, stats, grDevices Suggests: sp, maps, maptools, testthat License: GPL-3 Copyright: All code is Copyright (C) Michael Hahsler and Kurt Hornik. NeedsCompilation: yes Packaged: 2020-02-20 19:33:51 UTC; hahsler Author: Michael Hahsler [aut, cre, cph], Kurt Hornik [aut, cph] Maintainer: Michael Hahsler Repository: CRAN Date/Publication: 2020-02-21 06:50:16 UTC TSP/build/0000755000176200001440000000000013623557437012036 5ustar liggesusersTSP/build/vignette.rds0000644000176200001440000000031113623557437014370 0ustar liggesusersb```b`fcd`b2 1# 'f  +G+)O)M.S(W*æ % Ml ba DX%Z]?4-ީE0=(jؠjX2sR,s\ܠL t7`~΢r=xA$Gs=ʕXVr7}TSP/tests/0000755000176200001440000000000012676120024012062 5ustar liggesusersTSP/tests/testthat/0000755000176200001440000000000013623676650013740 5ustar liggesusersTSP/tests/testthat/test-ETSP.R0000644000176200001440000000070513612366100015575 0ustar liggesuserslibrary(TSP) library(testthat) context("ETSP") x <- data.frame(x = runif(20), y = runif(20), row.names = LETTERS[1:20]) ## create a TSP etsp <- ETSP(x) etsp ## use some methods expect_equal(n_of_cities(etsp), 20L) expect_equal(labels(etsp), LETTERS[1:20]) ## solve tour <- solve_TSP(etsp) tour ## compare tour_length expect_equal(tour_length(etsp), tour_length(as.TSP(etsp))) expect_equal(tour_length(tour, etsp), tour_length(tour, as.TSP(etsp))) TSP/tests/testthat/test-concorde.R0000644000176200001440000000457313612366100016625 0ustar liggesuserslibrary(TSP) library(testthat) context("solve_TSP (Concorde and Linkern)") m <- rbind( c(0, 1, 0, 1), c(1, 0, 1, Inf), c(0, 1, 0, 1), c(1, Inf, 1, 0) ) d <- as.dist(m) tsp <- TSP(d) tsp skip_if_not( Sys.which("concorde") != "" && Sys.which("linkern") != "", message = "skipped test for concorde/linkern. Not installed.") o <- solve_TSP(tsp, method="concorde") expect_equivalent(tour_length(tsp, o), 4) # large numbers should be scaled right. o_large <- solve_TSP(tsp*2^15, method="concorde") expect_equivalent(o, o_large) o_large <- solve_TSP(tsp*10^10, method="concorde") expect_equivalent(o, o_large) # expect warning for rounding expect_warning(o_large <- solve_TSP(tsp*2^15+0.1, method="concorde")) expect_equivalent(o, o_large) # expect a warning for rounding expect_warning(o_round <- solve_TSP(tsp/0.3, method="concorde")) expect_equivalent(o, o_round) o <- solve_TSP(tsp, method="linkern") expect_equivalent(tour_length(tsp, o), 4) # test ATSP #data <- matrix(runif(5^2), ncol = 5, dimnames = list(1:5, 1:5)) data <- structure(c(0.13930352916941, 0.897691324818879, 0.509101516567171, 0.430898967897519, 0.141799068776891, 0.0334562903735787, 0.902805947931483, 0.203576791565865, 0.435874363640323, 0.0641707226168364, 0.101683554705232, 0.631239329231903, 0.555331876967102, 0.0829615572001785, 0.272443652851507, 0.215095571940765, 0.532841097796336, 0.795302660670131, 0.43256876245141, 0.582661165855825, 0.250269076088443, 0.164849652675912, 0.638499777996913, 0.857200765516609, 0.0134391817264259), .Dim = c(5L, 5L), .Dimnames = list( c("1", "2", "3", "4", "5"), c("1", "2", "3", "4", "5"))) atsp <- ATSP(data) ## Concorde (gives conversation warning for reformulation of ATSP to TSP) expect_warning(o1 <- solve_TSP(atsp, method = "concorde")) o2 <- solve_TSP(atsp, method = "concorde", as_TSP = TRUE) expect_equal(length(o1), 5L) expect_equal(length(o2), 5L) # Concorde should find the optimal solution of 0.8082826 expect_equal(round(tour_length(o1), 7), 0.8082826) expect_equal(round(tour_length(o2), 7), 0.8082826) ## Linkern expect_warning(o1 <- solve_TSP(atsp, method = "linkern")) o2 <- solve_TSP(atsp, method = "linkern", as_TSP = TRUE) expect_equal(length(o1), 5L) expect_equal(length(o2), 5L) # Linkern should find the optimal solution of 0.8082826 expect_equal(round(tour_length(o1), 7), 0.8082826) expect_equal(round(tour_length(o2), 7), 0.8082826) TSP/tests/testthat/test-solve_TSP.R0000644000176200001440000000451713514544532016715 0ustar liggesuserslibrary(TSP) library(testthat) context("solve_TSP") m <- rbind( c(0, 1, 0, 1), c(1, 0, 1, Inf), c(0, 1, 0, 1), c(1, Inf, 1, 0) ) d <- as.dist(m) tsp <- TSP(d) tsp ## from matrix should give the same result expect_equal(as.numeric(tsp), as.numeric(TSP(as.matrix(d)))) ## test error on NA tsp_na <- tsp tsp_na[4] <- NA expect_error(o <- solve_TSP(tsp_na)) ## test Inf methods <- c("nearest_insertion", "cheapest_insertion", "farthest_insertion", "arbitrary_insertion", "nn", "repetitive_nn", "two_opt", "random", "identity") tours <- lapply(methods, FUN = function(m) solve_TSP(tsp, method = m)) names(tours) <- methods #tours tl <- sapply(tours, attr, "tour_length") expect_true(all(tl == 4 | tl == Inf)) ## test rep res <- solve_TSP(tsp, rep=10) tl <- attr("res", "tour_length") expect_true(all(tl == 4 | tl == Inf)) ## no two_opt res <- solve_TSP(tsp, two_opt=FALSE) tl <- attr("res", "tour_length") expect_true(all(tl == 4 | tl == Inf)) ## test special case: two cities d <- dist(rbind(c(0,0), c(1,1))) tsp2 <- TSP(d) tours2 <- lapply(methods, FUN = function(m) solve_TSP(tsp2, method = m)) expect_true(all(sapply(tours2, attr, "tour_length") == as.numeric(d)*2)) ## test special case: one city tsp1 <- TSP(dist(1)) tours1 <- lapply(methods, FUN = function(m) solve_TSP(tsp1, method = m)) expect_true(all(sapply(tours1, attr, "tour_length") == 0)) ## test ATSP (just for errors) #data <- matrix(runif(5^2), ncol = 5, dimnames = list(1:5, 1:5)) data <- structure(c(0.13930352916941, 0.897691324818879, 0.509101516567171, 0.430898967897519, 0.141799068776891, 0.0334562903735787, 0.902805947931483, 0.203576791565865, 0.435874363640323, 0.0641707226168364, 0.101683554705232, 0.631239329231903, 0.555331876967102, 0.0829615572001785, 0.272443652851507, 0.215095571940765, 0.532841097796336, 0.795302660670131, 0.43256876245141, 0.582661165855825, 0.250269076088443, 0.164849652675912, 0.638499777996913, 0.857200765516609, 0.0134391817264259), .Dim = c(5L, 5L), .Dimnames = list( c("1", "2", "3", "4", "5"), c("1", "2", "3", "4", "5"))) # best solution is 0.8082826 atsp <- ATSP(data) methods <- c("nearest_insertion", "cheapest_insertion", "farthest_insertion", "arbitrary_insertion", "nn", "repetitive_nn", "two_opt", "random", "identity") tours <- lapply(methods, FUN = function(m) solve_TSP(atsp, method = m)) names(tours) <- methods TSP/tests/testthat/test-insert_cut_etc.R0000644000176200001440000000112712676234052020044 0ustar liggesuserslibrary("testthat") library("TSP") data("USCA50") context("insert_dummy") tsp <- insert_dummy(USCA50, label = "cut") expect_equal(n_of_cities(tsp), n_of_cities(USCA50) + 1L) expect_equal(labels(tsp), c(labels(USCA50), "cut")) context("cut_tour") tour <- solve_TSP(tsp) ## cut tour into path at the dummy city path <- cut_tour(tour, "cut") expect_equal(length(path), n_of_cities(USCA50)) context("reformulate") ## reformualte atsp <- as.ATSP(USCA50) expect_equal(tour_length(USCA50), tour_length(atsp)) tsp <- reformulate_ATSP_as_TSP(atsp) expect_equal(n_of_cities(atsp)*2, n_of_cities(tsp)) TSP/tests/testthat/test-TSPLIB.R0000644000176200001440000000174312676124153016033 0ustar liggesuserslibrary(TSP) library(testthat) context("TSPLIB") set.seed(1234) x <- data.frame(x=runif(5), y=runif(5)) ## create TSP, ATSP and ETSP (2D) d <- round(dist(x), 3) ## TSP tsp <- TSP(d) tsp write_TSPLIB(tsp, file="example.tsp", precision = 6) #file.show("example.tsp") r <- read_TSPLIB("example.tsp", precision = 6) expect_equivalent(tsp, r) ## ATSP atsp <- ATSP(d) atsp write_TSPLIB(atsp, file="example.tsp", precision = 6) #file.show("example.tsp") r <- read_TSPLIB("example.tsp", precision = 6) expect_equivalent(atsp, r) ## ETSP (2D) etsp <- ETSP(round(x[,1:2], 3)) etsp write_TSPLIB(etsp, file="example.tsp", precision = 6) #file.show("example.tsp") r <- read_TSPLIB("example.tsp", precision = 6) expect_equivalent(etsp, r) ## Infinity d[2] <- Inf tsp <- TSP(d) write_TSPLIB(tsp, file="example.tsp", precision = 6) r <- read_TSPLIB("example.tsp", precision = 6) expect_equivalent(tsp[-2], r[-2]) expect_more_than(r[2], range(tsp, finite = TRUE)[2]) ## clean up unlink("example.tsp") TSP/tests/testthat.R0000644000176200001440000000007012676120023014041 0ustar liggesuserslibrary("testthat") library("TSP") test_check("TSP") TSP/src/0000755000176200001440000000000013623557437011526 5ustar liggesusersTSP/src/tour_length.c0000644000176200001440000000513713271504171014214 0ustar liggesusers#include #include #include "matrix_pos.h" typedef enum {false = 0, true = 1} bool; /* * Calculate the tour length given a distance matrix and a permuation vector */ SEXP tour_length_dist(SEXP R_dist, SEXP R_order) { double tour_length = 0.0; SEXP R_tour_length; double segment; bool posinf = false; bool neginf = false; int *order = INTEGER(R_order); int n = INTEGER(getAttrib(R_dist, install("Size")))[0]; double *dist = REAL(R_dist); if (n != LENGTH(R_order)) error("length of distance matrix and tour do not match"); for (int i = 0; i < (n-1); i++) { segment = dist[LT_POS(n, order[i]-1, order[i+1]-1)]; // check Inf if (segment == R_PosInf) posinf = true; else if (segment == R_NegInf) neginf = true; else tour_length += segment; } // close tour if (n > 1) { segment = dist[LT_POS(n, order[n-1]-1, order[0]-1)]; // check Inf if (segment == R_PosInf) posinf = true; else if (segment == R_NegInf) neginf = true; else tour_length += segment; // inf if (posinf && neginf) tour_length = NA_REAL; else if (posinf) tour_length = R_PosInf; else if (neginf) tour_length = R_NegInf; } // create R object PROTECT(R_tour_length = NEW_NUMERIC(1)); REAL(R_tour_length)[0] = tour_length; UNPROTECT(1); return R_tour_length; } /* * Calculate tour length form a matrix */ SEXP tour_length_matrix(SEXP R_matrix, SEXP R_order) { double tour_length = 0.0; SEXP R_tour_length; double segment; bool posinf = false; bool neginf = false; int n = INTEGER(GET_DIM(R_matrix))[0]; double *matrix = REAL(R_matrix); int *order = INTEGER(R_order); if (n != LENGTH(R_order)) error("length of distance matrix and tour do not match"); for (int i = 0; i < (n-1); i++) { segment = matrix[M_POS(n, order[i]-1, order[i+1]-1)]; // check inf first if (segment == R_PosInf) posinf = true; else if (segment == R_NegInf) neginf = true; else tour_length += segment; } // close tour segment = matrix[M_POS(n, order[n-1]-1, order[0]-1)]; // check inf first if (segment == R_PosInf) posinf = true; else if (segment == R_NegInf) neginf = true; else tour_length += segment; // inf if (posinf && neginf) tour_length = NA_REAL; else if (posinf) tour_length = R_PosInf; else if (neginf) tour_length = R_NegInf; PROTECT(R_tour_length = NEW_NUMERIC(1)); REAL(R_tour_length)[0] = tour_length; UNPROTECT(1); return R_tour_length; } TSP/src/matrix_pos.h0000644000176200001440000000072312606077054014056 0ustar liggesusers /* LT_POS to access a lower triangle matrix by C. Buchta * modified by M. Hahsler * n ... number of rows/columns * i,j ... column and row index [0, (n-1)] * * Note: does not cover the case i==j! */ #ifndef LT_POS #define LT_POS(n, i, j) \ (i)<(j) ? (n*(i) - ((i)+1)*(i)/2 + (j)-(i)) -1 \ : (n*(j) - ((j+1))*(j)/2 + (i)-(j)) -1 #endif /* * access for matrix */ #ifndef M_POS #define M_POS(rows, i, j) \ (i) + (j)*(rows) #endif TSP/src/dll.c0000644000176200001440000000237113053150677012440 0ustar liggesusers #include #include #include extern SEXP two_opt(SEXP R_matrix, SEXP R_t); extern SEXP two_opt_sym(SEXP R_matrix, SEXP R_t); extern SEXP insertion_cost(SEXP R_matrix, SEXP R_order, SEXP R_k); extern SEXP tour_length_dist(SEXP R_dist, SEXP R_order); extern SEXP tour_length_matrix(SEXP R_matrix, SEXP R_order); void R_init_TSP(DllInfo *dll) { const R_CallMethodDef CallEntries[] = { {"R_two_opt", (DL_FUNC) two_opt, 2}, {"R_two_opt_sym", (DL_FUNC) two_opt_sym, 2}, {"R_insertion_cost", (DL_FUNC) insertion_cost, 3}, {"R_tour_length_dist", (DL_FUNC) tour_length_dist, 2}, {"R_tour_length_matrix", (DL_FUNC) tour_length_matrix, 2}, {NULL, NULL, 0} }; R_registerRoutines(dll, NULL, CallEntries, NULL, NULL); R_useDynamicSymbols(dll, FALSE); R_RegisterCCallable("arules", "R_two_opt", (DL_FUNC) two_opt); R_RegisterCCallable("arules", "R_two_opt_sym", (DL_FUNC) two_opt_sym); R_RegisterCCallable("arules", "R_insertion_cost", (DL_FUNC) insertion_cost); R_RegisterCCallable("arules", "R_tour_length_dist", (DL_FUNC) tour_length_dist); R_RegisterCCallable("arules", "R_tour_length_matrix", (DL_FUNC) tour_length_matrix); } TSP/src/insertion_cost.c0000644000176200001440000000372212606077054014730 0ustar liggesusers#include #include #include "matrix_pos.h" /* * Calculate insertion cost for the insertion algorithms */ SEXP insertion_cost(SEXP R_matrix, SEXP R_order, SEXP R_k) { int n = INTEGER(GET_DIM(R_matrix))[0]; int length = LENGTH(R_order); int *order = INTEGER(R_order); int k = INTEGER(R_k)[0]-1; SEXP R_cost; PROTECT(R_cost = NEW_NUMERIC(length)); double link_add1, link_add2, link_remove; double *matrix = REAL(R_matrix); double *cost = REAL(R_cost); if (length == 1) { cost[0] = matrix[M_POS(n, order[0]-1, k)]; }else{ for (int i = 0; i < (length-1); i++) { link_add1 = matrix[M_POS(n, order[i]-1, k)]; link_add2 = matrix[M_POS(n, k, order[i+1]-1)]; link_remove = matrix[M_POS(n, order[i]-1, order[i+1]-1)]; //Rprintf("Links: %f %f %f\n", link_add1, link_add2, link_remove); // check for infinity if(link_add1 == R_NegInf || link_add2 == R_NegInf || link_remove == R_PosInf) cost[i] = R_NegInf; else if(link_add1 == R_PosInf || link_add2 == R_PosInf || link_remove == R_NegInf) cost[i] = R_PosInf; else cost[i] = link_add1 + link_add2 - link_remove; } link_add1 = matrix[M_POS(n, order[length-1]-1, k)]; link_add2 = matrix[M_POS(n, k, order[0]-1)]; link_remove = matrix[M_POS(n, order[length-1]-1, order[0]-1)]; // check for infinity if(link_add1 == R_PosInf || link_add2 == R_PosInf) cost[length-1] = R_PosInf; else if(link_remove == R_PosInf) cost[length-1] = R_NegInf; // removing a inf is very good else cost[length-1] = link_add1 + link_add2 - link_remove; } UNPROTECT(1); return R_cost; } TSP/src/two_opt.c0000644000176200001440000001271513612366100013352 0ustar liggesusers #include #include #include "matrix_pos.h" //#define TWOOPT_DEBUG 1 // only improvements >EPSILON are used #define EPSILON 1.0e-7 /* 2-opt * * R_matrix ... matrix with distances * R_t .. initial tour * * inf and NA is not allowed! * */ // this implementation also works for asymetric TSPs SEXP two_opt(SEXP R_matrix, SEXP R_t) { int i, j, n; int swaps; int swap1, swap2; double imp, imp_tmp, imp_best; int tmp; double *matrix = REAL(R_matrix); // make a copy of the initial tour (Note: t is 1-based) int *t = INTEGER(R_t = PROTECT(duplicate(R_t))); // check n = INTEGER(GET_DIM(R_matrix))[0]; if (LENGTH(R_t) != n) error("tour has invalid length"); for (i = 0; i < n; i++) if (t[i] < 1 || t[i] > n) error("tour contains invalid values"); // main loop do{ swaps = 0; swap1 = swap2 = 0; imp_best = 0.0; // find the swap with largest improvement // i is first city to swap (0-based index) for (i = 1; i < n-1; i++){ imp = 0.0; // add gains for getting to the first city (i-1 -> i) imp += matrix[M_POS(n, t[i-1]-1, t[i]-1)]; // gains by adding one more city to the swap imp += matrix[M_POS(n, t[i]-1, t[i+1]-1)]; // j is the last city to swap (0-based index) for (j = i+1; j < n-1; j++){ // gains by adding one more city to the swap imp += matrix[M_POS(n, t[j]-1, t[j+1]-1)]; // increased cost for one more city imp -= matrix[M_POS(n, t[j]-1, t[j-1]-1)]; // include gains from closing the tour (i-1 -> j and i -> j+1) imp_tmp = imp - matrix[M_POS(n, t[i-1]-1, t[j]-1)] - matrix[M_POS(n, t[i]-1, t[j+1]-1)]; if(imp_tmp > EPSILON) { swaps++; if(imp_tmp > imp_best) { imp_best = imp_tmp; swap1 = i; swap2 = j; } } } // check the last city (needs distance to first city) j = n-1; // increased cost for one more city imp -= matrix[M_POS(n, t[j]-1, t[j-1]-1)]; // include gains from closing the tour (this time with first city) imp_tmp = imp - matrix[M_POS(n, t[i-1]-1, t[j]-1)] - matrix[M_POS(n, t[i]-1, t[0]-1)]; // check improvement if(imp_tmp > EPSILON) { swaps++; if(imp_tmp > imp_best) { imp_best = imp_tmp; swap1 = i; swap2 = j; } } } #ifdef TWOOPT_DEBUG printf("two_opt: %d possible swaps\n", swaps); #endif // reverse sub-tour if(swaps > 0){ #ifdef TWOOPT_DEBUG printf("two_opt: best improvement is %f\n", imp_best); printf("two_opt: reversing cities %d to %d\n", swap1+1, swap2+1); #endif for(i = 0; i < (swap2-swap1+1)/2; i++) { // +1 for even length tmp = t[swap1+i]; t[swap1+i] = t[swap2-i]; t[swap2-i] = tmp; } } R_CheckUserInterrupt(); }while (swaps > 0); UNPROTECT(1); return R_t; } // this implementation only works for symetric TSPs // Note: code is slightly faster than the code above but is not unused SEXP two_opt_sym(SEXP R_matrix, SEXP R_t) { int i, j, n; int swaps; int swap1, swap2; double e1, e2, e1_swap, e2_swap; double imp, cur_imp; int tmp; double *matrix = REAL(R_matrix); // make a copy of the initial tour int *t = INTEGER(R_t = PROTECT(duplicate(R_t))); // check n = INTEGER(GET_DIM(R_matrix))[0]; if (LENGTH(R_t) != n) error("tour has invalid length"); for (i = 0; i < n; i++) { if (t[i] < 1 || t[i] > n) error("tour contains invalid values"); } // main loop do{ swaps = 0; swap1 = swap2 = 0; imp = 0.0; // find the swap with largest improvement (works only for symetric TSPs) for (i = 0; i < (n-2); i++){ e1 = matrix[M_POS(n, t[i]-1, t[i+1]-1)]; for (j = (i+1); j < (n-1); j++){ e2 = matrix[M_POS(n, t[j]-1, t[j+1]-1)]; e1_swap = matrix[M_POS(n, t[i]-1, t[j]-1)]; e2_swap = matrix[M_POS(n, t[i+1]-1, t[j+1]-1)]; /* // handle pos inf (now handled in R code) if (e1_swap == R_PosInf || e2_swap == R_PosInf) cur_imp = 0; else if (e1 == R_PosInf || e2 == R_PosInf) cur_imp = R_PosInf; else */ cur_imp = (e1+e2) - (e1_swap+e2_swap); if(cur_imp > 0) { swaps++; if(cur_imp > imp) { imp = cur_imp; swap1 = i+1; swap2 = j; } } } // check the last city (needs distance to first city) e2 = matrix[M_POS(n, t[n-1]-1, t[0]-1)]; e1_swap = matrix[M_POS(n, t[i]-1, t[n-1]-1)]; e2_swap = matrix[M_POS(n, t[i+1]-1, t[0]-1)]; cur_imp = (e1+e2) - (e1_swap+e2_swap); // check improvement if(cur_imp > 0) { swaps++; if(cur_imp > imp) { imp = cur_imp; swap1 = i+1; swap2 = n-1; } } } #ifdef TWOOPT_DEBUG printf("two_opt: %d possible swaps\n", swaps); #endif // reverse sub-tour if(swaps > 0){ #ifdef TWOOPT_DEBUG printf("two_opt: best improvement is %f\n", imp); printf("two_opt: swapping %d to %d\n", swap1, swap2); #endif for(i = 0; i < (swap2-swap1+1)/2; i++) { // +1 for even length tmp = t[swap1+i]; t[swap1+i] = t[swap2-i]; t[swap2-i] = tmp; } } R_CheckUserInterrupt(); }while (swaps >0); UNPROTECT(1); return R_t; } TSP/vignettes/0000755000176200001440000000000013623557437012747 5ustar liggesusersTSP/vignettes/TSP.Rnw0000644000176200001440000013174513623555613014112 0ustar liggesusers%\documentclass[10pt,a4paper,fleqn]{article} \documentclass[nojss]{jss} \usepackage[english]{babel} %% my packages %\usepackage{a4wide} %\usepackage[round,longnamesfirst]{natbib} %\usepackage{hyperref} % \usepackage{amsmath} \usepackage{amsfonts} % %\newcommand{\strong}[1]{{\normalfont\fontseries{b}\selectfont #1}} \newcommand{\class}[1]{\mbox{\textsf{#1}}} \newcommand{\func}[1]{\mbox{\texttt{#1()}}} %\newcommand{\code}[1]{\mbox{\texttt{#1}}} %\newcommand{\pkg}[1]{\strong{#1}} \newcommand{\samp}[1]{`\mbox{\texttt{#1}}'} %\newcommand{\proglang}[1]{\textsf{#1}} \newcommand{\set}[1]{\mathcal{#1}} %\usepackage{Sweave} %% \VignetteIndexEntry{Introduction to TSP} \author{Michael Hahsler\\Southern Methodist University \And Kurt Hornik\\Wirtschaftsuniversit\"at Wien} \title{\pkg{TSP} -- Infrastructure for the Traveling Salesperson Problem} %% for pretty printing and a nice hypersummary also set: \Plainauthor{Michael Hahsler, Kurt Hornik} %% comma-separated \Plaintitle{TSP -- Infrastructure for the Traveling Salesperson Problem} %% without formatting \Shorttitle{Infrastructure for the TSP} %% a short title (if necessary) %% an abstract and keywords \Abstract{ The traveling salesperson problem (also known as traveling salesman problem or TSP) is a well known and important combinatorial optimization problem. The goal is to find the shortest tour that visits each city in a given list exactly once and then returns to the starting city. Despite this simple problem statement, solving the TSP is difficult since it belongs to the class of NP-complete problems. The importance of the TSP arises besides from its theoretical appeal from the variety of its applications. Typical applications in operations research include vehicle routing, computer wiring, cutting wallpaper and job sequencing. The main application in statistics is combinatorial data analysis, e.g., reordering rows and columns of data matrices or identifying clusters. In this paper we introduce the \proglang{R}~package \pkg{TSP} which provides a basic infrastructure for handling and solving the traveling salesperson problem. The package features S3 classes for specifying a TSP and its (possibly optimal) solution as well as several heuristics to find good solutions. In addition, it provides an interface to \emph{Concorde}, one of the best exact TSP solvers currently available. } \Keywords{combinatorial optimization, traveling salesman problem, \proglang{R}} \Plainkeywords{combinatorial optimization, traveling salesman problem, R} %% without formatting %% The address of (at least) one author should be given %% in the following format: \Address{ Michael Hahsler\\ Engineering Management, Information, and Systems\\ Lyle School of Engineering\\ Southern Methodist University\\ P.O. Box 750123 \\ Dallas, TX 75275-0123\\ E-mail: \email{mhahsler@lyle.smu.edu}\\ Kurt Hornik\\ Department of Finance, Accounting and Statistics\\ Wirtschaftsuniversit\"at Wien\\ 1090 Wien, Austria\\ E-mail: \email{kurt.hornik@wu-wien.ac.at}\\ URL: \url{http://statmath.wu.ac.at/~hornik/} } \begin{document} <>= options(width = 75, useFancyQuotes=FALSE, prompt="R> ") ### for sampling set.seed(1234) @ %\title{Introduction to \pkg{TSP} -- Infrastructure for the Traveling % Salesperson Problem} %\author{Michael Hahsler and Kurt Hornik} \maketitle \sloppy %\abstract{ % The traveling salesperson (or, salesman) problem (TSP) is a % well known and important combinatorial optimization problem. The goal % is to find the shortest tour that visits each city in a given list % exactly once and then returns to the starting city. Despite this % simple problem statement, solving the TSP is difficult since it % belongs to the class of NP-complete problems. The importance of the % TSP arises besides from its theoretical appeal from the variety of its % applications. Typical applications in operations research include % vehicle routing, computer wiring, cutting wallpaper and job % sequencing. The main application in statistics is combinatorial data % analysis, e.g., reordering rows and columns of data matrices or % identifying clusters. In this paper we introduce the % \proglang{R}~package \pkg{TSP} which provides a basic infrastructure % for handling and solving the traveling salesperson problem. The % package features S3 classes for specifying a TSP and its (possibly % optimal) solution as well as several heuristics to find good % solutions. In addition, it provides an interface to \emph{Concorde}, % one of the best exact TSP solvers currently available. } \section{Introduction} The traveling salesperson problem~\citep[TSP;][]{Lawler1985, Gutin2002} is a well known and important combinatorial optimization problem. The goal is to find the shortest tour that visits each city in a given list exactly once and then returns to the starting city. Formally, the TSP can be stated as follows. The distances between $n$ cities are stored in a distance matrix $\mathbf{D}$ with elements $d_{ij}$ where $i,j = 1\dots n$ and the diagonal elements $d_{ii}$ are zero. A \emph{tour} can be represented by a cyclic permutation $\pi$ of $\{1, 2,\dots, n\}$ where $\pi(i)$ represents the city that follows city $i$ on the tour. The traveling salesperson problem is then the optimization problem to find a permutation $\pi$ that minimizes the \emph{length of the tour} denoted by \begin{equation} \sum_{i=1}^n d_{i\pi(i)}. \end{equation} % see Lenstra & Kan 1975: Some simple Applications to the TSP For this minimization task, the tour length of $(n-1)!$ permutation vectors have to be compared. This results in a problem which is very hard to solve and in fact known to be NP-complete~\citep{Johnson1985a}. However, solving TSPs is an important part of applications in many areas including vehicle routing, computer wiring, machine sequencing and scheduling, frequency assignment in communication networks~\citep{Lenstra1975, Punnen2002}. %and structuring of %matrices~\citep{Lenstra1975, Punnen2002}. Applications in statistical data analysis include ordering and clustering objects. For example, data analysis applications in psychology ranging from profile smoothing to finding an order in developmental data are presented by~\cite{Hubert1978}. Clustering and ordering using TSP solvers is currently becoming popular in biostatistics. For example, \cite{Ray2007} describe an application for ordering genes and \cite{Johnson2006} use a TSP solver for clustering proteins. In this paper we give a very brief overview of the TSP and introduce the \proglang{R}~package \pkg{TSP} which provides an infrastructure for handling and solving TSPs. The paper is organized as follows. In Section~\ref{sec:TSP} we briefly present important aspects of the TSP including different problem formulations and approaches to solve TSPs. In Section~\ref{sec:infrastructure} we give an overview of the infrastructure implemented in \pkg{TSP} and the basic usage. In Section~\ref{sec:examples}, several examples are used to illustrate the package's capabilities. Section~\ref{sec:conclusion} concludes the paper. A previous version of this manuscript was published in the \emph{Journal of Statistical Software} \citep{TSP:Hahsler+Hornik2007}. \section{Theory} \label{sec:TSP} In this section, we briefly summarize some aspects of the TSP which are important for the implementation of the \pkg{TSP} package described in this paper. For a complete treatment of all aspects of the TSP, we refer the interested reader to the classic book edited by \cite{Lawler1985} and the more modern book edited by \cite{Gutin2002}. It has to be noted that in this paper, following the origin of the TSP, the term \emph{distance} is used. Distance is used here interchangeably with dissimilarity or cost and, unless explicitly stated, no restrictions to measures which obey the triangle inequality are made. An important distinction can be made between the symmetric TSP and the more general asymmetric TSP. For the symmetric case (normally referred to as just \emph{TSP}), for all distances in $\mathbf{D}$ the equality $d_{ij} = d_{ji}$ holds, i.e., it does not matter if we travel from $i$ to $j$ or the other way round, the distance is the same. In the asymmetric case (called \emph{ATSP}), the distances are not equal for all pairs of cities. Problems of this kind arise when we do not deal with spatial distances between cities but, e.g., with the cost or necessary time associated with traveling between locations, where the price for the plane ticket between two cities may be different depending on which way we go. \subsection{Different formulations of the TSP} \label{sec:formulations} Other than the permutation problem in the introduction, the TSP can also be formulated as a graph theoretic problem. Here the TSP is formulated by means of a complete graph $G = (V, E)$, where the cities correspond to the node set $V = \{1,2,\ldots,n\}$ and each edge $e_i \in E$ has an associated weight $w_i$ representing the distance between the nodes it connects. If the graph is not complete, the missing edges can be replaced by edges with very large distances. The goal is to find a \emph{Hamiltonian cycle}, i.e., a cycle which visits each node in the graph exactly once, with the least weight in the graph~\citep{Hoffman1985}. This formulation naturally leads to procedures involving minimum spanning trees for tour construction or edge exchanges to improve existing tours. TSPs can also be represented as integer and linear programming problems~\citep[see, e.g.,][]{Punnen2002}. The \emph{integer programming (IP) formulation} is based on the assignment problem with additional constraint of no sub-tours: \[ \begin{array}{rl} \text{Minimize } & \sum_{i=1}^n\sum_{j=1}^n{d_{ij}x_{ij}} % = \mathrm{trace}(\mathbf{D}^T\mathbf{X}) \\[3mm] \text{Subject to } & \sum_{i=1}^n{x_{ij}=1}, \quad j=1,\ldots,n, \\ & \sum_{j=1}^n{x_{ij}=1}, \quad i=1,\ldots,n, \\ & x_{ij} = 0 \text{ or } 1 \\ & \text{no sub-tours allowed} \\ \end{array} \] The solution matrix $\mathbf{X} = (x_{ij})$ of the assignment problem represents a tour or a collection of sub-tour (several unconnected cycles) where only edges which corresponding to elements $x_{ij} = 1$ are on the tour or a sub-tour. The additional restriction that no sub-tours are allowed (called \emph{sub-tour elimination constraints}) restrict the solution to only proper tours. Unfortunately, the number of sub-tour elimination constraints grows exponentially with the number of cities which leads to an extremely hard problem. The \emph{linear programming (LP) formulation} of the TSP is given by: \[ \begin{array}{rl} \text{Minimize } & \sum_{i=1}^m{w_ix_i} = \mathbf{w}^T\mathbf{x}\\[3mm] \text{Subject to } & \mathbf{x} \in \mathcal{S} \\ \end{array} \] where $m$ is the number of edges $e_i$ in $G$, $w_i \in \mathbf{w}$ is the weight of edge $e_i$ and $\mathbf{x}$ is the incidence vector indicating the presence or absence of each edge in the tour. Again, the constraints given by $\mathbf{x} \in \mathcal{S}$ are problematic since they have to contain the set of incidence vectors of all possible Hamiltonian cycles in $G$ which amounts to a direct search of all $(n-1)!$ possibilities and thus in general is infeasible. However, relaxed versions of the linear programming problem with removed integrality and sub-tour elimination constraints are extensively used by modern TSP solvers where such a partial description of constraints is used and improved iteratively in a branch-and-bound approach. \subsection{Useful manipulations of the distance matrix} \label{sec:manipulations} Sometimes it is useful to transform the distance matrix $\mathbf{D} = (d_{ij})$ of a TSP into a different matrix $\mathbf{D'} = (d'_{ij})$ which has the same optimal solution. Such a transformation requires that for any Hamiltonian cycle $H$ in a graph represented by its distance matrix $\mathbf{D}$ the equality \begin{equation*} \sum_{i,j \in H}{d_{ij}} = \alpha \sum_{i,j \in H}{d'_{ij}} + \beta \end{equation*} holds for suitable $\alpha > 0$ and $\beta \in \mathbb{R}$. From the equality we see that additive and multiplicative constants leave the optimal solution invariant. This property is useful to rescale distances, e.g., for many solvers, distances in the interval $[0, 1]$ have to be converted into integers from~1 to a maximal value. A different manipulation is to reformulate an asymmetric TSP as a symmetric TSP. This is possible by doubling the number of cities~\citep{Jonker1983}. For each city a dummy city is added. Between each city and its corresponding dummy city a very small value (e.g., $-\infty$) is used. This makes sure that each city always occurs in the solution together with its dummy city. The original distances are used between the cities and the dummy cities, where each city is responsible for the distance going to the city and the dummy city is responsible for the distance coming from the city. The distances between all cities and the distances between all dummy cities are set to a very large value (e.g., $\infty$) which makes these edges infeasible. An example for equivalent formulations as an asymmetric TSP (to the left) and a symmetric TSP (to the right) for three cities is: \begin{equation*} \begin{pmatrix} 0 &d_{12} &d_{13} \\ d_{21} &0 &d_{23} \\ d_{31} &d_{32} &0 \\ \end{pmatrix} \Longleftrightarrow \begin{pmatrix} 0 &\infty &\infty & -\infty &d_{21} &d_{31} \\ \infty &0 &\infty & d_{12} &-\infty &d_{31} \\ \infty &\infty &0 & d_{13} &d_{23} &-\infty \\ -\infty &d_{12} &d_{13} & 0 &\infty &\infty \\ d_{21} &-\infty &d_{23} & \infty &0 &\infty \\ d_{31} &d_{32} &-\infty & \infty &\infty &0 \\ \end{pmatrix} \end{equation*} Instead of the infinity values suitably large negative and positive values can be used. The new symmetric TSP can be solved using techniques for symmetric TSPs which are currently far more advanced than techniques for ATSPs. Removing the dummy cities from the resulting tour gives the solution for the original ATSP. \subsection{Finding exact solutions for the TSP} \label{sec:exact} Finding the exact solution to a TSP with $n$ cities requires to check $(n-1)!$ possible tours. To evaluate all possible tours is infeasible for even small TSP instances. To find the optimal tour \cite{Held1962} presented the following \emph{dynamic programming} formulation: Given a subset of city indices (excluding the first city) $S \subset \{2, 3, \dots, n\}$ and $l \in S$, let $d^*(S, l)$ denote the length of the shortest path from city $1$ to city $l$, visiting all cities in $S$ in-between. For $S = \{l\}$, $d^*(S,l)$ is defined as $d_{1l}$. The shortest path for larger sets with $|S| > 1$ is \begin{equation} d^*(S,l) = \mathrm{min}_{m \in S\setminus\{l\}}\Bigl( d^*(S\setminus\{l\},m) + d_{ml}\Bigl). %\text{ for } |S| > 1. \end{equation} Finally, the minimal tour length for a complete tour which includes returning to city $1$ is \begin{equation} d^{**} = \mathrm{min}_{l \in \{2,3,\dots,n\}}\Bigl( d^*(\{2,3,\dots,n\}, l) + d_{l1}\Bigl). \end{equation} Using the last two equations, the quantities $d^*(S,l)$ can be computed recursively and the minimal tour length $d^{**}$ can be found. In a second step, the optimal permutation $\pi = \{1, i_2, i_3,\dots,i_n\}$ of city indices $1$ through $n$ can be computed in reverse order, starting with $i_n$ and working successively back to $i_2$. The procedure exploits the fact that a permutation $\pi$ can only be optimal, if \begin{equation} d^{**} = d^*(\{2,3,\dots,n\}, i_n) + d_{i_n1} \end{equation} and, for $2 \le p \le n-1$, \begin{equation} d^*(\{i_2, i_3,\dots, i_p, i_{p+1}\}, i_{p+1}) = d^*(\{i_2,i_3,\dots,i_p\}, i_p) + d_{i_pi_{p+1}}. \end{equation} The space complexity of storing the values for all $d^*(S,l)$ is $(n-1)2^{n-2}$ which severely restricts the dynamic programming algorithm to TSP problems of small sizes. However, for very small TSP instances this approach is fast and efficient. %\marginpar{time complexity if order $n^22^n$. Check!} A different method, which can deal with larger instances, uses a relaxation of the linear programming problem presented in Section~\ref{sec:formulations} and iteratively tightens the relaxation till a solution is found. This general method for solving linear programming problems with complex and large inequality systems is called \emph{cutting plane method} and was introduced by \cite{Dantzig1954}. Each iteration begins with using instead of the original linear inequality description $\mathcal{S}$ the relaxation $A\mathbf{x} \le b$, where the polyhedron $P$ defined by the relaxation contains $\mathcal{S}$ and is bounded. The optimal solution $\mathbf{x}^*$ of the relaxed problem can be obtained using standard linear programming solvers. If the $\mathbf{x}^*$ found belongs to $\mathcal{S}$, the optimal solution of the original problem is obtained, otherwise, a linear inequality can be found which is satisfied by all points in $\mathcal{S}$ but violated by $\mathbf{x}^*$. Such an inequality is called a cutting plane or cut. A family of such cutting planes can be added to the inequality system $A\mathbf{x} \le b$ to obtain a tighter relaxation for the next iteration. If no further cutting planes can be found or the improvement in the objective function due to adding cuts gets very small, the problem is branched into two sub-problems which can be minimized separately. Branching is done iteratively which leads to a binary tree of sub-problems. Each sub-problem is either solved without further branching or is found to be irrelevant because its relaxed version already produces a longer path than a solution of another sub-problem. This method is called \emph{branch-and-cut}~\citep{Padberg1990} which is a variation of the well known \emph{branch-and-bound}~\citep{Land1960} procedure. The initial polyhedron $P$ used by \cite{Dantzig1954} contains all vectors $\mathbf{x}$ for which all $x_e \in \mathbf{x}$ satisfy $0 \le x_e \le 1$ and in the resulting tour each city is linked to exactly two other cities. Various separation algorithms for finding subsequent cuts to prevent sub-tours (\emph{sub-tour elimination inequalities}) and to ensure an integer solution \citep[\emph{Gomory cuts;}][]{Gomory1963} were developed over time. The currently most efficient implementation of this method is \emph{Concorde} described in~\cite{Applegate2000}. \subsection{Heuristics for the TSP} \label{sec:heuristics} The NP-completeness of the TSP already makes it more time efficient for small-to-medium size TSP instances to rely on heuristics in case a good but not necessarily optimal solution is sufficient. TSP heuristics typically fall into two groups, tour construction heuristics which create tours from scratch and tour improvement heuristics which use simple local search heuristics to improve existing tours. In the following we will only discuss heuristics available in \pkg{TSP}, for a comprehensive overview of the multitude of TSP heuristics including an experimental comparison, we refer the reader to the book chapter by \cite{Johnson2002}. \subsubsection{Tour construction heuristics} The implemented tour construction heuristics are the nearest neighbor algorithm and the insertion algorithms. \paragraph{Nearest neighbor algorithm.} The nearest neighbor algorithm~\citep{Rosenkrantz1977} follows a very simple greedy procedure: The algorithm starts with a tour containing a randomly chosen city and then always adds to the last city in the tour the nearest not yet visited city. The algorithm stops when all cities are on the tour. An extension to this algorithm is to repeat it with each city as the starting point and then return the best tour found. This heuristic is called repetitive nearest neighbor. \paragraph{Insertion algorithms.} All insertion algorithms~\citep{Rosenkrantz1977} start with a tour consisting of an arbitrary city and then choose in each step a city $k$ not yet on the tour. This city is inserted into the existing tour between two consecutive cities $i$ and $j$, such that the insertion cost (i.e., the increase in the tour's length) $$d(i,k) + d(k,j) - d(i,j)$$ is minimized. The algorithms stop when all cities are on the tour. The insertion algorithms differ in the way the city to be inserted next is chosen. The following variations are implemented: \begin{description} \item[Nearest insertion] The city $k$ is chosen in each step as the city which is nearest to a city on the tour. \item[Farthest insertion] The city $k$ is chosen in each step as the city which is farthest from any of the cities on the tour. \item[Cheapest insertion] The city $k$ is chosen in each step such that the cost of inserting the new city is minimal. \item[Arbitrary insertion] The city $k$ is chosen randomly from all cities not yet on the tour. \end{description} The nearest and cheapest insertion algorithms correspond to the minimum spanning tree algorithm by \cite{Prim1957}. Adding a city to a partial tour corresponds to adding an edge to a partial spanning tree. For TSPs with distances obeying the triangular inequality, the equality to minimum spanning trees provides a theoretical upper bound for the two algorithms of twice the optimal tour length. The idea behind the farthest insertion algorithm is to link cities far outside into the tour first to establish an outline of the whole tour early. With this change, the algorithm cannot be directly related to generating a minimum spanning tree and thus the upper bound stated above cannot be guaranteed. However, it can was shown that the algorithm generates tours which approach $2/3$ times the optimal tour length~\citep{Johnson1985}. \subsubsection{Tour improvement heuristics} Tour improvement heuristics are simple local search heuristics which try to improve an initial tour. A comprehensive treatment of the topic can be found in the book chapter by \cite{Rego2002}. \paragraph{$k$-Opt heuristics.} The idea is to define a neighborhood structure on the set of all admissible tours. Typically, a tour $t'$ is a neighbor of another tour $t$ if $t'$ can be obtained from $t$ by deleting $k$ edges and replacing them by a set of different feasible edges (a $k$-Opt move). In such a structure, the tour can iteratively be improved by always moving from one tour to its best neighbor till no further improvement is possible. The resulting tour represents a local optimum which is called $k$-optimal. Typically, $2$-Opt~\citep{Croes1958} and $3$-Opt~\citep{Lin1965} heuristics are used in practice. \paragraph{Lin-Kernighan heuristic.} This heuristic~\citep{Lin1973} does not use a fixed value for $k$ for its $k$-Opt moves, but tries to find the best choice of $k$ for each move. The heuristic uses the fact that each $k$-Opt move can be represented as a sequence of $2$-Opt moves. It builds up a sequence of $2$-Opt moves, checking after each additional move whether a stopping rule is met. Then the part of the sequence which gives the best improvement is used. This is equivalent to a choice of one $k$-Opt move with variable $k$. Such moves are used till a local optimum is reached. By using full backtracking, the optimal solution can always be found, but the running time would be immense. Therefore, only limited backtracking is allowed in the procedure, which helps to find better local optima or even the optimal solution. Further improvements to the procedure are described by \cite{Lin1973}. \section{Computational infrastructure: the TSP package} \label{sec:infrastructure} In package~\pkg{TSP}, a traveling salesperson problem is defined by an object of class \class{TSP} (symmetric) or \class{ATSP} (asymmetric). \func{solve\_TSP} is used to find a solution, which is represented by an object of class \class{TOUR}. Figure~\ref{fig:overview} gives an overview of this infrastructure. \begin{figure} \centering \includegraphics[width=14cm]{overview} \caption{An overview of the classes in \pkg{TSP}.} \label{fig:overview} \end{figure} \class{TSP} objects can be created from a distance matrix (a \class{dist} object) or a symmetric matrix using the creator function \func{TSP} or coercion with \func{as.TSP}. Similarly, \class{ATSP} objects are created by \func{ATSP} or \func{as.ATSP} from square matrices representing the distances. In the creation process, labels are taken and stored as city names in the object or can be explicitly given as arguments to the creator functions. Several methods are defined for the classes: \begin{itemize} \item \func{print} displays basic information about the problem (number of cities and the distance measure employed). \item \func{n\_of\_cities} returns the number of cities. \item \func{labels} returns the city names. \item \func{image} produces a shaded matrix plot of the distances between cities. The order of the cities can be specified as the argument \code{order}. \end{itemize} Internally, an object of class \class{TSP} is a \class{dist} object with an additional class attribute and, therefore, if needed, can be coerced to \class{dist} or to a matrix. An \class{ATSP} object is represented as a square matrix. Obviously, asymmetric TSPs are more general than symmetric TSPs, hence, symmetric TSPs can also be represented as asymmetric TSPs. To formulate an asymmetric TSP as a symmetric TSP with double the number of cities (see Section \ref{sec:manipulations}), \func{reformulate\_ATSP\_as\_TSP} is provided. This function creates the necessary dummy cities and adapts the distance matrix accordingly. A popular format to save TSP descriptions to disk which is supported by most TSP solvers is the format used by \emph{TSPLIB}, a library of sample instances of the TSP maintained by \cite{Reinelt2004}. The \pkg{TSP} package provides \func{read\_TSPLIB} and \func{write\_TSPLIB} to read and save symmetric and asymmetric TSPs in TSPLIB format. Class \class{TOUR} represents a solution to a TSP by an integer permutation vector containing the ordered indices and labels of the cities to visit. In addition, it stores an attribute indicating the length of the tour. Again, suitable \func{print} and \func{labels} methods are provided. The raw permutation vector (i.e., the order in which cities are visited) can be obtained from a tour using \func{as.integer}. With \func{cut\_tour}, a circular tour can be split at a specified city resulting in a path represented by a vector of city indices. The length of a tour can always be calculated using \func{tour\_length} and specifying a TSP and a tour. Instead of the tour, an integer permutation vector calculated outside the \pkg{TSP} package can be used as long as it has the correct length. All TSP solvers in \pkg{TSP} can be used with the simple common interface: \begin{quote} \code{solve\_TSP(x, method, control)} \end{quote} where \code{x} is the TSP to be solved, \code{method} is a character string indicating the method used to solve the TSP and \code{control} can contain a list with additional information used by the solver. The available algorithms are shown in Table~\ref{tab:methods}. \begin{table} \caption{Available algorithms in \pkg{TSP}.} \label{tab:methods} \centering \begin{tabular}{llc} \hline \textbf{Algorithm} & \textbf{Method argument} & \textbf{Applicable to} \\ \hline Nearest neighbor algorithm & \code{"nn"} & TSP/ATSP \\ Repetitive nearest neighbor algorithm & \code{"repetitive\_nn"} & TSP/ATSP \\ Nearest insertion & \code{"nearest\_insertion"} & TSP/ATSP \\ Farthest insertion & \code{"farthest\_insertion"} & TSP/ATSP \\ Cheapest insertion & \code{"cheapest\_insertion"} & TSP/ATSP \\ Arbitrary insertion & \code{"arbitrary\_insertion"} & TSP/ATSP \\ Concorde TSP solver & \code{"concorde"} & TSP \\ 2-Opt improvement heuristic & \code{"two\_opt"} & TSP/ATSP \\ Chained Lin-Kernighan & \code{"linkern"} & TSP \\ \hline \end{tabular} \end{table} All algorithms except the Concorde TSP solver and the Chained Lin-Kernighan heuristic (a Lin-Kernighan variation described in \cite{Applegate2003}) are included in the package and distributed under the GNU Public License (GPL). For the Concorde TSP solver and the Chained Lin-Kernighan heuristic only a simple interface (using \func{write\_TSPLIB}, calling the executable and reading back the resulting tour) is included in \pkg{TSP}. The executable itself is part of the Concorde distribution, has to be installed separately and is governed by a different license which allows only for academic use. The interfaces are included since Concorde~\citep{Applegate2000,Applegate2006} is currently one of the best implementations for solving symmetric TSPs based on the branch-and-cut method discussed in section~\ref{sec:exact}. In May 2004, Concorde was used to find the optimal solution for the TSP of visiting all 24,978 cities in Sweden. The computation was carried out on a cluster with 96 Xeon 2.8 GHz nodes and took in total almost 100 CPU years. \section{Examples} \label{sec:examples} In this section we provide some examples for the use of package~\pkg{TSP}. We start with a simple example of how to use the interface of the TSP solver to compare different heuristics. Then we show how to solve related tasks, using the Hamiltonian shortest path problem as an example. Finally, we give an example of clustering using the \pkg{TSP} package. An additional application can be found in package \pkg{seriation}~\citep{TSP:Hahsler+Buchta+Hornik:2006} which uses the TSP solvers from \pkg{TSP} to order (seriate) objects given a proximity matrix. \subsection{Comparing some heuristics} In the following example, we use several heuristics to find a short path in the \code{USCA50} data set which contains the distances between the first 50 cities in the \code{USCA312} data set. The \code{USCA312} data set contains the distances between 312 cities in the USA and Canada coded as a symmetric TSP. The smaller data set is used here, since some of the heuristic solvers employed are rather slow. <<>>= library("TSP") data("USCA50") USCA50 @ We calculate tours using different heuristics and store the results in the list \code{tours}. As an example, we show the first tour which displays the method employed, the number of cities involved and the tour length. All tour lengths are compared using the dot chart in Figure~\ref{fig:dotchart}. For the chart, we add a point for the optimal solution which has a tour length of 14497. The optimal solution can be found using Concorde (\code{method = "concorde"}). It is omitted here, since Concorde has to be installed separately. <>= set.seed(1234) @ <>= methods <- c("nearest_insertion", "farthest_insertion", "cheapest_insertion", "arbitrary_insertion", "nn", "repetitive_nn", "two_opt") tours <- sapply(methods, FUN = function(m) solve_TSP(USCA50, method = m), simplify = FALSE) ## tours$concorde <- solve_TSP(tsp, method = "concorde") tours[[1]] dotchart(sort(c(sapply(tours, tour_length), optimal = 14497)), xlab = "tour length", xlim = c(0, 20000)) @ \begin{figure} \centering \includegraphics[width=11cm, trim=0 10 0 0]{TSP-dotchart_USCA50} \caption{Comparison of the tour lengths for the USCA50 data set.} \label{fig:dotchart} \end{figure} \subsection{Finding the shortest Hamiltonian path} The problem of finding the shortest Hamiltonian path through a graph (i.e., a path which visits each node in the graph exactly once) can be transformed into the TSP with cities and distances representing the graphs vertices and edge weights, respectively~\citep{Garfinkel1985}. Finding the shortest Hamiltonian path through all cities disregarding the endpoints can be achieved by inserting a `dummy city' which has a distance of zero to all other cities. The position of this city in the final tour represents the cutting point for the path. In the following we use a heuristic to find a short path in the \code{USCA312} data set. Inserting dummy cities is performed in \pkg{TSP} by \func{insert\_dummy}. <>= set.seed(1234) @ <<>>= library("TSP") data("USCA312") tsp <- insert_dummy(USCA312, label = "cut") tsp @ The TSP now contains an additional dummy city and we can try to solve this TSP. <<>>= tour <- solve_TSP(tsp, method="farthest_insertion") tour @ Since the dummy city has distance zero to all other cities, the path length is equal to the tour length reported above. The path starts with the first city in the list after the `dummy' city and ends with the city right before it. We use \func{cut\_tour} to create a path and show the first and last 6 cities on it. <<>>= path <- cut_tour(tour, "cut") head(labels(path)) tail(labels(path)) @ The tour found in the example results in a path from Lihue on Hawaii to Prince Rupert in British Columbia. Such a tour can also be visualized using the packages \pkg{sp}, \pkg{maps} and \pkg{maptools} \citep{TSP:Pebesma+Bivand:2005}. Note that he \code{if} statement and the \code{plot} in the \code{else} part in the following is not needed and only checks if the appropriate packages are installed when building this document. <>= if(require(sp) && require(maps) && require(maptools)) { library("sp") library("maps") library("maptools") data("USCA312_GPS") # create spatial coordinates and a basemap using WGS84 projection. USCA312_coords <- SpatialPointsDataFrame(cbind(USCA312_GPS$long, USCA312_GPS$lat), proj4string=CRS("+proj=longlat +datum=WGS84"), data = USCA312_GPS) USCA312_basemap <- map2SpatialLines(map("world", xlim=c(-166,-47), ylim=c(15,83), plot=FALSE), proj4string=CRS("+proj=longlat +datum=WGS84")) plot_path <- function(path){ plot(as(USCA312_coords, "Spatial"), axes = TRUE) plot(USCA312_basemap, add = TRUE, col = "gray") points(USCA312_coords, pch = 3, cex = 0.4, col = "red") path_line <- SpatialLines(list(Lines(list(Line(USCA312_coords[path,])), ID="1"))) plot(path_line, add=TRUE, col = "black") points(USCA312_coords[c(head(path,1), tail(path,1)),], pch = 19, col = "black") } plot_path(path) } else { plot(NA, xlim= c(0,1), ylim = c(0,1)); text(.5, .5, "Suggested packages not available") } @ \begin{figure} \centering \includegraphics[width=10cm, trim=0 30 0 0]{TSP-map1} \caption{A ``short'' Hamiltonian path for the USCA312 dataset.} \label{fig:map1} \end{figure} The map containing the path is presented in Figure~\ref{fig:map1}. It has to be mentioned that the path found by the used heuristic is considerable longer than the optimal path found by Concorde with a length of $34928$, illustrating the power of modern TSP algorithms. For the following two examples, we indicate how the distance matrix between cities can be modified to solve related shortest Hamiltonian path problems. These examples serve as illustrations of how modifications can be made to transform different problems into a TSP. The first problem is to find the shortest Hamiltonian path starting with a given city. In this case, all distances to the selected city are set to zero, forcing the evaluation of all possible paths starting with this city and disregarding the way back from the final city in the tour. By modifying the distances the symmetric TSP is changed into an asymmetric TSP (ATSP) since the distances between the starting city and all other cities are no longer symmetric. As an example, we choose New York as the starting city. We transform the data set into an ATSP and set the column corresponding to New York to zero before solving it. Thus, the distance to return from the last city in the path to New York does not contribute to the path length. We use the nearest neighbor heuristic to calculate an initial tour which is then improved using $2$-Opt moves and cut at New York to create a path. <>= set.seed(1234) @ <<>>= atsp <- as.ATSP(USCA312) ny <- which(labels(USCA312) == "New York, NY") atsp[, ny] <- 0 initial_tour <- solve_TSP(atsp, method="nn") initial_tour tour <- solve_TSP(atsp, method ="two_opt", control = list(tour = initial_tour)) tour path <- cut_tour(tour, ny, exclude_cut = FALSE) head(labels(path)) tail(labels(path)) @ <>= plot_path(path) @ \begin{figure} \centering \includegraphics[width=10cm, trim=0 30 0 0]{TSP-map2} \caption{A Hamiltonian path for the USCA312 dataset starting in New York.} \label{fig:map2} \end{figure} The found path is presented in Figure~\ref{fig:map2}. It begins with New York and cities in New Jersey and ends in a city in Manitoba, Canada. %The path shows the typical behavior %of the nearest neighbor heuristic with first connecting the cities close by and %then making rather big ``jumps'' for the final cities. Concorde and many advanced TSP solvers can only solve symmetric TSPs. To use these solvers, we can formulate the ATSP as a TSP using \func{reformulate\_ATSP\_as\_TSP} which introduces a dummy city for each city (see Section~\ref{sec:manipulations}). <<>>= tsp <- reformulate_ATSP_as_TSP(atsp) tsp @ After finding a tour for the TSP, the dummy cities are removed again giving the tour for the original ATSP. Note that the tour needs to be reversed if the dummy cities appear before and not after the original cities in the solution of the TSP. The following code is not executed here, since it takes several minutes to execute and Concorde has to be installed separately. Concorde finds the optimal solution with a length of $36091$. <>= tour <- solve_TSP(tsp, method = "concorde") tour <- as.TOUR(tour[tour <= n_of_cities(atsp)]) @ Finding the shortest Hamiltonian path which ends in a given city can be achieved likewise by setting the row in the distance matrix which corresponds to this city to zero. For finding the shortest Hamiltonian path we can also restrict both end points. This problem can be transformed to a TSP by replacing the two cities by a single city which contains the distances from the start point in the columns and the distances to the end point in the rows. Obviously this is again an asymmetric TSP. For the following example, we are only interested in paths starting in New York and ending in Los Angeles. Therefore, we remove the two cities from the distance matrix, create an asymmetric TSP and insert a dummy city called \code{"LA/NY"}. The distances from this dummy city are replaced by the distances from New York and the distances towards are replaced by the distances towards Los Angeles. <>= set.seed(1234) @ <<>>= m <- as.matrix(USCA312) ny <- which(labels(USCA312) == "New York, NY") la <- which(labels(USCA312) == "Los Angeles, CA") atsp <- ATSP(m[-c(ny,la), -c(ny,la)]) atsp <- insert_dummy(atsp, label = "LA/NY") la_ny <- which(labels(atsp) == "LA/NY") atsp[la_ny, ] <- c(m[-c(ny,la), ny], 0) atsp[, la_ny] <- c(m[la, -c(ny,la)], 0) @ We use the nearest insertion heuristic. <<>>= tour <- solve_TSP(atsp, method ="nearest_insertion") tour path_labels <- c("New York, NY", labels(cut_tour(tour, la_ny)), "Los Angeles, CA") path_ids <- match(path_labels, labels(USCA312)) head(path_labels) tail(path_labels) @ <>= plot_path(path_ids) @ The path jumps from New York to cities in Ontario and it passes through cities in California and Nevada before ending in Los Angeles. The path displayed in Figure~\ref{fig:map3} contains multiple crossings which indicate that the solution is suboptimal. The optimal solution generated by reformulating the problem as a TSP and using Concorde has only a tour length of $38489$. \begin{figure} \centering \includegraphics[width=10cm, trim=0 30 0 0]{TSP-map3} \caption{A Hamiltonian path for the USCA312 dataset starting in New York and ending in Los Angles.} \label{fig:map3} \end{figure} \subsection{Rearrangement clustering} Solving a TSP to obtain a clustering was suggested several times in the literature \citep[see, e.g.,][]{Lenstra1974, Alpert1997, Johnson2004}. The idea is that objects in clusters are visited in consecutive order and from one cluster to the next larger ``jumps'' are necessary. \cite{Climer2006} call this type of clustering \emph{rearrangement clustering} and suggest to automatically find the cluster boundaries of $k$ clusters by adding $k$ \emph{dummy cities} which have constant distance $c$ to all other cities and are infinitely far from each other. In the optimal solution of the TSP, the dummy cities must separate the most distant cities and thus represent optimal boundaries for $k$ clusters. For the following example, we use the well known iris data set. Since we know that the dataset contains three classes denoted by the variable \code{Species}, we insert three dummy cities into the TSP for the iris data set and perform rearrangement clustering using the default method (nearest insertion algorithm). Note that this algorithm does not find the optimal solution and it is not guaranteed that the dummy cities will present the best cluster boundaries. %\marginpar{FIXME: Was sagt Concorde dazu?} <>= set.seed(4444) @ <<>>= data("iris") tsp <- TSP(dist(iris[-5]), labels = iris[, "Species"]) tsp_dummy <- insert_dummy(tsp, n = 3, label = "boundary") tour <- solve_TSP(tsp_dummy) @ Next, we plot the TSP's permuted distance matrix using shading to represent distances. The result is displayed as Figure~\ref{fig:clustering}. Lighter areas represent larger distances. The additional red lines represent the positions of the dummy cities in the tour, which mark the cluster boundaries obtained. <>= ## plot the distance matrix image(tsp_dummy, tour, xlab = "objects", ylab ="objects") ## draw lines where the dummy cities are located abline(h = which(labels(tour)=="boundary"), col = "red") abline(v = which(labels(tour)=="boundary"), col = "red") @ \begin{figure} \centering \includegraphics[width=9cm, height=9cm, trim=0 20 0 0]{TSP-clustering} \caption{Result of rearrangement clustering using three dummy cities and the nearest insertion algorithm on the iris data set.} \label{fig:clustering} \end{figure} One pair of red horizontal and vertical lines exactly separates the darker from lighter areas. The second pair occurs inside the larger dark block. We can look at how well the partitioning obtained fits the structure in the data given by the species field in the data set. Since we used the species as the city labels in the TSP, the labels in the tour represent the partitioning with the dummy cities named `boundary' separating groups. The result can be summarized based on the run length encoding of the obtained tour labels: <<>>= out <- rle(labels(tour)) data.frame(Species = out$values, Lenghts = out$lengths, Pos = cumsum(out$lengths)) @ One boundary perfectly splits the iris data set into a group containing only examples of species `Setosa' and a second group containing examples for `Virginica' and `Versicolor'. However, the second boundary only separates several examples of species `Virginica' from other examples of the same species. Even in the optimal tour found by Concorde, this problem occurs. The reason why the rearrangement clustering fails to split the data into three groups is the closeness between the groups `Virginica' and `Versicolor'. To inspect this problem further, we can project the data points on the first two principal components of the data set and add the path segments which resulted from solving the TSP. <>= prc <- prcomp(iris[1:4]) plot(prc$x, pch = as.numeric(iris[,5]), col = as.numeric(iris[,5])) paths <- cut_tour(tour, cut = "boundary") for(p in paths) lines(prc$x[p, ]) @ \begin{figure} \centering \includegraphics[width=10cm, trim=0 20 0 0]{TSP-clustering2} \caption{The 3 path segments representing a rearrangement clustering of the iris data set. The data points are projected on the set's first two principal components. The three species are represented by different markers and colors.} \label{fig:clustering2} \end{figure} The result in shown in Figure~\ref{fig:clustering2}. The three species are identified by different markers and all points connected by a single path represent a cluster found. Clearly, the two groups to the right side of the plot are too close to be separated correctly by using just the distances between individual points. This problem is similar to the \emph{chaining effect} known from hierarchical clustering using the single-linkage method. \section{Conclusion} \label{sec:conclusion} In this paper we presented the R extension package \pkg{TSP} which implements an infrastructure to handle and solve TSPs. The package introduces classes for problem descriptions (\class{TSP} and \class{ATSP}) and for the solution (\class{TOUR}). Together with a simple interface for solving TSPs, it allows for an easy and transparent usage of the package. With the interface to Concorde, \pkg{TSP} also can use a state of the art implementation which efficiently computes exact solutions using branch-and-cut. \section*{Acknowledgments} The authors of this paper want to thank Roger Bivand for providing the code to correctly draw tours and paths on a projected map. % %\bibliographystyle{abbrvnat} \bibliography{TSP} % \end{document} TSP/vignettes/TSP.bib0000644000176200001440000002704512606077054014073 0ustar liggesusers@INCOLLECTION{Garfinkel1985, author = {R.S. Garfinkel}, title = {Motivation and Modeling}, year = {1985}, chapter = {2}, pages = {17--36}, crossref = {Lawler1985}, owner = {hahsler}, timestamp = {2006.11.06} } @INCOLLECTION{Hoffman1985, author = {A.J. Hoffman and P. Wolfe}, title = {History}, year = {1985}, chapter = {1}, pages = {1--16}, crossref = {Lawler1985}, owner = {hahsler} } @INCOLLECTION{Johnson2002, author = {D.S. Johnson and L.A. McGeoch}, title = {Experimental Analysis of Heuristics for the {STSP}}, year = {2002}, chapter = {9}, pages = {369--444}, crossref = {Gutin2002}, owner = {hahsler}, timestamp = {2006.12.07} } @INCOLLECTION{Johnson1985, author = {D.S. Johnson and C.H. Papadimitriou}, title = {Performance guarantees for heuristics}, year = {1985}, chapter = {5}, pages = {145--180}, crossref = {Lawler1985}, owner = {hahsler}, timestamp = {2006.10.06} } @INCOLLECTION{Johnson1985a, author = {D.S. Johnson and C.H. Papadimitriou}, title = {Computational complexity}, year = {1985}, chapter = {3}, pages = {37--86}, crossref = {Lawler1985}, owner = {hahsler}, timestamp = {2006.10.06} } @INCOLLECTION{Punnen2002, author = {A.P. Punnen}, title = {The Traveling Salesman Problem: Applications, Formulations and Variations}, year = {2002}, chapter = {1}, pages = {1--28}, crossref = {Gutin2002}, owner = {hahsler}, timestamp = {2006.12.06} } @INCOLLECTION{Rego2002, author = {C. Rego and F. Glover}, title = {Local Search and Metaheuristics}, year = {2002}, chapter = {8}, pages = {309--368}, crossref = {Gutin2002}, owner = {hahsler}, timestamp = {2006.12.06} } @ARTICLE{Alpert1997, author = {C. J. Alpert and A. B. Kahng}, title = {Splitting an Ordering into a Partititon to Minimize Diameter}, journal = {Journal of Classification}, year = {1997}, volume = {14}, pages = {51--74}, number = {1}, owner = {hahsler}, timestamp = {2006.12.19} } @MANUAL{Applegate2006, title = {Concorde {TSP} Solver}, author = {David Applegate and Robert Bixby and Vasek Chv{\'a}tal and William Cook}, year = {2006}, owner = {hahsler}, timestamp = {2006.10.06}, url = {http://www.tsp.gatech.edu/concorde/} } @ARTICLE{Applegate1998, author = {David Applegate and Robert Bixby and Vasek Chv{\'a}tal and William Cook}, title = {On the Solution of Traveling Salesman Problems}, journal = {Documenta Mathematica}, year = {1998}, volume = {Extra Volume ICM}, pages = {645--656}, owner = {hahsler}, timestamp = {2006.10.06} } @INPROCEEDINGS{Applegate2000, author = {David Applegate and Robert E. Bixby and Vasek Chv{\'a}tal and William Cook}, title = {{TSP} Cuts Which Do Not Conform to the Template Paradigm}, booktitle = {Computational Combinatorial Optimization, Optimal or Provably Near-Optimal Solutions}, year = {2000}, editor = {M. Junger and D. Naddef}, volume = {2241}, series = {Lecture Notes In Computer Science}, pages = {261--304}, address = {London, UK}, publisher = {Springer-Verlag}, owner = {hahsler}, timestamp = {2006.10.06} } @ARTICLE{Applegate2003, author = {David Applegate and William Cook and Andre Rohe}, title = {Chained {L}in-{K}ernighan for Large Traveling Salesman Problems}, journal = {{INFORMS} Journal on Computing}, year = {2003}, volume = {15}, pages = {82--92}, number = {1}, owner = {hahsler} } @ARTICLE{Climer2006, author = {Sharlee Climer and Weixiong Zhang}, title = {Rearrangement Clustering: Pitfalls, Remedies, and Applications}, journal = {Journal of Machine Learning Research}, year = {2006}, volume = {7}, pages = {919--943}, month = jun, owner = {hahsler}, timestamp = {2006.10.06} } @ARTICLE{Croes1958, author = {G. A. Croes}, title = {A Method for Solving Traveling-Salesman Problems}, journal = {Operations Research}, year = {1958}, volume = {6}, pages = {791--812}, number = {6}, owner = {hahsler}, timestamp = {2006.11.29} } @ARTICLE{Dantzig1954, author = {G.B. Dantzig and D.R. Fulkerson and S.M. Johnson}, title = {Solution of a Large-scale Traveling Salesman Problem}, journal = {Operations Research}, year = {1954}, volume = {2}, pages = {393--410}, owner = {hahsler}, timestamp = {2006.12.10} } @INPROCEEDINGS{Gomory1963, author = {R.E. Gomory}, title = {An algorithm for integer solutions to linear programs}, booktitle = {Recent Advances in Mathematical Programming}, year = {1963}, editor = {R.L. Graves and P. Wolfe}, pages = {269--302}, address = {New York}, publisher = {McGraw-Hill}, owner = {hahsler}, timestamp = {2006.12.10} } @TECHREPORT{Hahsler2007a, author = {Michael Hahsler and Kurt Hornik and Christian Buchta}, title = {Getting Things in Order: An Introduction to the {R} package seriation}, institution = {Research Report Series, Department of Statistics and Mathematics, Wirtschaftsuniversit{\"a}t Wien}, year = {2007}, type = {Report}, number = {58}, address = {Augasse 2--6, 1090 Wien, Austria}, month = {August}, owner = {hahsler}, timestamp = {2007.12.04} } @ARTICLE{Held1962, author = {M. Held and R.M. Karp}, title = {A Dynamic Programming Approach to Sequencing Problems}, journal = {Journal of {SIAM}}, year = {1962}, volume = {10}, pages = {196--210}, owner = {hahsler}, timestamp = {2006.11.27} } @ARTICLE{Hubert1978, author = {Lawrence J. Hubert and Frank B. Baker}, title = {Applications of Combinatorial Programming to Data Analysis: The Traveling Salesman and Related Problems}, journal = {Psychometrika}, year = {1978}, volume = {43}, pages = {81--91}, number = {1}, month = {March}, owner = {hahsler}, timestamp = {2007.12.04} } @INPROCEEDINGS{Johnson2004, author = {David Johnson and Shankar Krishnan and Jatin Chhugani and Subodh Kumar and Suresh Venkatasubramanian}, title = {Compressing Large Boolean Matrices Using Reordering Techniques}, booktitle = {Proceedings of the 30th VLDB Conference}, year = {2004}, pages = {13--23}, owner = {hahsler}, timestamp = {2006.12.19} } @ARTICLE{Johnson2006, author = {Olin Johnson and Jing Liu}, title = {A traveling salesman approach for predicting protein functions}, journal = {Source Code for Biology and Medicine}, year = {2006}, volume = {1}, pages = {1--7}, number = {3}, owner = {hahsler}, timestamp = {2007.11.28} } @ARTICLE{Jonker1983, author = {Jonker, R. and Volgenant, T.}, title = {Transforming asymmetric into symmetric traveling salesman problems}, journal = {Operations Research Letters}, year = {1983}, volume = {2}, pages = {161--163}, owner = {hahsler}, timestamp = {2006.12.05} } @INPROCEEDINGS{Kruskal1956, author = {J.B. Kruskal}, title = {On the shortest spanning subtree and the traveling salesman problem}, booktitle = {Proceedings of the American Mathematical Society}, year = {1956}, pages = {48--50}, owner = {hahsler}, timestamp = {2006.10.06} } @ARTICLE{Land1960, author = {A.H. Land and A.G. Doig}, title = {An Automatic Method for Solving Discrete Programming Problems}, journal = {Econometrica}, year = {1960}, volume = {28}, pages = {497--520}, owner = {hahsler}, timestamp = {2006.12.12} } @ARTICLE{Lenstra1975, author = {J.K. Lenstra and A.H.G. Rinooy Kan}, title = {Some simple applications of the travelling salesman problem}, journal = {Operational Research Quarterly}, year = {1975}, volume = {26}, pages = {717--733}, number = {4}, month = {November}, owner = {hahsler}, timestamp = {2006.11.07} } @ARTICLE{Lenstra1974, author = {J. K. Lenstra}, title = {Clustering a Data Array and the Traveling-Salesman Problem}, journal = {Operations Research}, year = {1974}, volume = {22}, pages = {413--414}, number = {2}, owner = {hahsler}, timestamp = {2006.12.19} } @ARTICLE{Lin1965, author = {S. Lin}, title = {Computer solutions of the traveling-salesman problem}, journal = {Bell System Technology Journal}, year = {1965}, volume = {44}, pages = {2245--2269}, owner = {hahsler}, timestamp = {2006.11.29} } @ARTICLE{Lin1973, author = {S. Lin and B.W. Kernighan}, title = {An effective heuristic algorithm for the traveling-salesman problem}, journal = {Operations Research}, year = {1973}, volume = {21}, pages = {498--516}, number = {2}, owner = {hahsler}, timestamp = {2006.11.27} } @ARTICLE{Padberg1990, author = {M. Padberg and G. Rinaldi}, title = {Facet identification for the symmetric traveling salesman polytope}, journal = {Mathematical Programming}, year = {1990}, volume = {47}, pages = {219--257}, number = {2}, address = {Secaucus, NJ, USA}, issn = {0025-5610}, publisher = {Springer-Verlag New York, Inc.} } @ARTICLE{Prim1957, author = {R.C. Prim}, title = {Shortest connection networks and some generalisations}, journal = {Bell System Technical Journal}, year = {1957}, volume = {36}, pages = {1389--1401}, owner = {hahsler}, timestamp = {2006.10.06} } @ARTICLE{Ray2007, author = {S. S. Ray and S. Bandyopadhyay and S. K. Pal}, title = {Gene Ordering in Partitive Clustering using Microarray Expressions}, journal = {Journal of Biosciences}, year = {2007}, volume = {32}, pages = {1019--1025}, number = {5}, month = {August}, owner = {hahsler}, timestamp = {2007.11.28} } @MANUAL{Reinelt2004, title = {{TSPLIB}}, author = {Gerhard Reinelt}, organization = {Universit{\"a}t Heidelberg, Institut f{\"u}r Informatik}, address = {Im Neuenheimer Feld 368,D-69120 Heidelberg, Germany}, year = {2004}, owner = {hahsler}, timestamp = {2006.10.06}, url = {http://www.iwr.uni-heidelberg.de/groups/comopt/software/TSPLIB95/} } @ARTICLE{Rosenkrantz1977, author = {Daniel J. Rosenkrantz and Richard E. Stearns and Philip M. Lewis, II}, title = {An Analysis of Several Heuristics for the Traveling Salesman Problem}, journal = {{SIAM} Journal on Computing}, year = {1977}, volume = {6}, pages = {563--581}, number = {3}, owner = {hahsler}, timestamp = {2006.11.13} } @BOOK{Gutin2002, title = {The Traveling Salesman Problem and Its Variations}, publisher = {Kluwer}, year = {2002}, editor = {G. Gutin and A.P. Punnen}, volume = {12}, series = {Combinatorial Optimization}, address = {Dordrecht}, owner = {hahsler}, timestamp = {2006.11.29} } @BOOK{Lawler1985, title = {The Traveling Salesman Problem}, publisher = {Wiley}, year = {1985}, editor = {Lawler, E. L. and Lenstra, J. K. and Rinnooy Kan, A. H. G. and Shmoys, D. B.}, address = {New York}, owner = {hahsler}, timestamp = {2006.10.05} } @comment{jabref-meta: selector_journal:} @comment{jabref-meta: selector_author:} @comment{jabref-meta: selector_keywords:} @comment{jabref-meta: selector_publisher:} @Manual{TSP:Hahsler+Buchta+Hornik:2006, title = {seriation: Infrastructure for seriation}, author = {Michael Hahsler and Christian Buchta and Kurt Hornik}, year = 2006, note = {R package version 0.1-1}, } @Article{TSP:Pebesma+Bivand:2005, author = {Edzer J. Pebesma and Roger S. Bivand}, title = {Classes and methods for spatial data in {R}}, journal = {R News}, year = 2005, volume = 5, number = 2, pages = {9--13}, month = {November}, url = {http://CRAN.R-project.org/doc/Rnews/}, } @ARTICLE{TSP:Hahsler+Hornik2007, AUTHOR = {Michael Hahsler and Kurt Hornik}, TITLE = {{TSP} -- {I}nfrastructure for the Traveling Salesperson Problem}, JOURNAL = {Journal of Statistical Software}, YEAR = {2007}, VOLUME = {23}, PAGES = {1-21}, NUMBER = {2}, MONTH = {December}, ISSN = {1548-7660} } TSP/vignettes/overview.odg0000644000176200001440000003027712606077054015311 0ustar liggesusersPKAOx5.++mimetypeapplication/vnd.oasis.opendocument.graphicsPKAOx5Configurations2/statusbar/PKAOx5'Configurations2/accelerator/current.xmlPKPKAOx5Configurations2/floater/PKAOx5Configurations2/popupmenu/PKAOx5Configurations2/progressbar/PKAOx5Configurations2/menubar/PKAOx5Configurations2/toolbar/PKAOx5Configurations2/images/Bitmaps/PKAOx5 content.xml\nߧm1BbK$] H& 3`$VGX,K퉓Ɖs\IyaGaYHk,ģ~̮_~R =rSo$Wf\[()XLLesoӽX\}3a0p5jl3`?d蟬.~`)XSG ߋ,6_!CߏHIŵ@ eN(ހ^aRUmM )>/ \Td[4ϹHnwrޢT5t08(-{ f4< DjGph,(zY߯W~h".] 2A [VlѵRR'6:s'ߔʕnhS_tMM eh߾5Ig*Y.*c X>˫[4X^*[,Y{s^H&>bNӞ.8Jʟ!8j7ʌ$mfm4= Y4?iWx:4_N6fdcsc' ]L}’]9Yz@ڲ.WîaW=~P:uqy;c N~vH=Z/__"44a$5mt1ރ(>w˅Qm8oG=fsJ}xE,4: ?tO!CGjۇξ%/S_J(A[8"I''("TtvQ..Sw-=u rV,2~AYjm,bq=`1b4$x{0( (# '3"<uI'Cgo!9o!d& !M3=>o4N;'Czq=!Bo3N3Ad@. f|W潸o}E͟\ݣ{I}y6^j_x囗w$͐LY㎙w)l@|Dۏ% 8"RҕI__RQ?V=^ȋ[zP&@uNjTݭWY'siiiON%'+'ɜÇIB, .钁&zYNaF'&*_8mFԥI? k(bnskrkzr?޴b#Omt4]C~FW/62U ltѝ7W3faKvC':1tbs[:* F90uI|YJѥά[2}gtWLIRj/׾AUpTN,LHW{0:S_T޻w5fI/H1ĤSOldV9hA MA™ R٭nach@#y(9be*xD,f;k L#0]zy%9]qz+gt[>xE!1bVUKhߎ ڕ*J VY~kw畦u_#}xxow9=l[|d EjrPRmmxC\ҘCyr92(rF؎#gőWN궢稜Yܴ> M-ٶ8T8Gu1m sxV`ƠM:UN[Q-NF'鳱lguChG|@:n~0mc()P- h) CB@PMCR}Lu8cC d hm3~LO8Mr#k`.ѳNwqZ'Y(tw%YX!4wjN8QVJ&a_ǫi-R>_ n;]n;BVk#q=kOViVZ8%ז#垡_ ڦ g۲f,u5Y,쇗:>7vu-ԛPK-<( LUPKAOx5 styles.xml\͎6)֏ev-hsAKDZ=$%xw݅ YsfęΘoȸ#<,Y6 ,vm0߾5 CU<&@8D$3@8V6shJpLW,%I)jrTzD=lbnJ r/ Kޖ, Y17C%/`P,B!C>S,M>͝ʲd?0ri)j_9W[$"rr&UDIަJIo dUSN2`s_{PS_wua>sUpWM].w@T+K9MJU)7R׵mҟ{N v,#B]c"w+c x{'t0EXl7ekEg `m9ۛ8ꎒO~mچm18x_rε2di1uL8Spfp%; cD+$YOCLh3wJg̦7WQ =bXro)XÒpA!iL e)ɌiV;lli"W@^ӈtm83/Je(f<>HlJR $ KdzUO4(# VfoV.:6|=R,biJ)~xOM'{4~-#ڒkKGJs*i=[F\\/j,6[ 4DpPǏ]S~ɑpu(EjURAToVI#u~%]Zʰ5X:uV$зv֞*=t NmW|n(Ag@ =ȤgqkpomK:~s+T}^hTqIiUT#˥rX`w&h6Lh 8* KDQ2"}6I,MZ/,:MG4 Fzm("D95 ;u>b~8D4cwϩ{1C40Iɨd6aD>+JL T>)r&DȻ"BjE"4BϫBjy/4N/ˌӎ}5f@ a9ۏJ8偿=XUOê#Zޱ lI"JQRՕE| A N5U; $,y1[DuOY= =Vjc5ִaNqe_G'lh˚DC%sh^uaQkEt7QsQU@m>_쩀0շk͔3RtZ^hpfT4Qre~.8ޕ_y8sn[)5Ho;;/Y"!r3iٌ|Ծ煭[:ұ_:Ko_:K~/}^~/~iY2є.Is{e֭ 06 3pՍ^,GWGЮ/ }|5ڽ09c]=7XWuXWuXW6Bc]}Zx|6RE(.rFgzї5y+/>8]g8FU%Fx> Zeˡ{Zf:QZDc?~mv. 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See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## create a TSP form an ATSP by doubling the cities reformulate_ATSP_as_TSP <- function(x, infeasible = Inf, cheap = -Inf) { if(!inherits(x, "ATSP")) stop("x is not an ATSP object!") method <- attr(x, "method") m <- as.matrix(x) ## scale matrix and add cheap links diag(m) <- cheap tsp <- rbind( cbind(matrix(infeasible, ncol = ncol(m), nrow = nrow(m)), t(m)), cbind(m, matrix(infeasible, ncol = nrow(m), nrow = ncol(m))) ) ## create labels (* for virtual cities) lab <- c(labels(x), paste(labels(x), "*", sep = "")) dimnames(tsp) <- list(lab, lab) attr(tsp, "method") <- method ## return as TSP TSP(tsp) } TSP/R/tsp_two_opt.R0000644000176200001440000000306013053151215013620 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## heuristic to improve a tour using exchanges of 2 edges. tsp_two_opt <- function(x, control = NULL){ control <- .get_parameters(control, list( tour = NULL, rep = 1 )) ## improve a given tour or create a random tour ## we use a function since for rep >1 we want several random ## initial tours initial <- function() { if(!is.null(control$tour)) as.integer(control$tour) else sample(n_of_cities(x)) } xx <- as.matrix(x) if(control$rep > 1) { tour <- replicate(control$rep, .Call(R_two_opt, xx, initial()), simplify = FALSE) lengths <- sapply(tour, FUN = function(t) tour_length(x, t)) tour <- tour[[which.min(lengths)]] }else tour <- .Call(R_two_opt, xx, initial()) tour } TSP/R/write_TSPLIB.R0000644000176200001440000000720713612366100013457 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## generic write_TSPLIB <- function(x, file, precision = 6, inf = NULL, neg_inf = NULL) UseMethod("write_TSPLIB") ## write a simple TSPLIB format file from an object of class TSP ## (contains a dist object or a symmetric matrix) ## TSP has data as integer write_TSPLIB.TSP <- function(x, file, precision = 6, inf = NULL, neg_inf = NULL) { ## prepare data (NA, Inf) if(any(is.na(x))) stop("NAs not allowed!") x <- .replaceInf(x, inf, neg_inf) ## Concorde can handle UPPER_ROW and dist (lower triangle matrix) ## is symmetric. format <- "EDGE_WEIGHT_FORMAT: UPPER_ROW" zz <- file(file, "w") cat("NAME: TSP", "COMMENT: Generated by write_TSPLIB (R-package TSP)", "TYPE: TSP", paste("DIMENSION:", n_of_cities(x)), "EDGE_WEIGHT_TYPE: EXPLICIT", format, file = zz, sep = "\n") ## only integers can be used as weights if(storage.mode(x) != "integer" && precision != 0) x <- x * 10^precision x <- suppressWarnings(as.integer(x)) if(any(is.na(x))) stop("Integer overflow, please reduce precision.") cat("EDGE_WEIGHT_SECTION", x, file = zz, sep = "\n") cat("EOF", file = zz, sep = "\n") close(zz) } write_TSPLIB.ATSP <- function(x, file, precision = 6, inf = NULL, neg_inf = NULL) { ## prepare data (NA, Inf) if(any(is.na(x))) stop("NAs not allowed!") x <- .replaceInf(x, inf, neg_inf) format <- "EDGE_WEIGHT_FORMAT: FULL_MATRIX" zz <- file(file, "w") cat("NAME: ATSP", "COMMENT: Generated by write_TSPLIB (R package TSP)", "TYPE: ATSP", paste("DIMENSION:", n_of_cities(x)), "EDGE_WEIGHT_TYPE: EXPLICIT", format, file = zz, sep = "\n") ## only integers can be used as weights if(storage.mode(x) != "integer") x <- x * 10^precision x <- suppressWarnings(as.integer(x)) if(any(is.na(x))) stop("integer overflow, please reduce precision.") cat("EDGE_WEIGHT_SECTION", x, file = zz, sep = "\n") cat("EOF", file = zz, sep = "\n") close(zz) } ## ETSP use data as real write_TSPLIB.ETSP <- function(x, file, precision = 6, inf = NULL, neg_inf = NULL) { if(any(is.na(x))) stop("NAs are not allowed!") if(any(!is.finite(x))) stop("Only finite values allowed!") if(ncol(x) == 2) type <- "EUC_2D" else if(ncol(x) == 3) type <- "EUC_3D" else stop("Only EUC_2D and EUC_3D supported.") zz <- file(file, "w") cat("NAME: ETSP", "COMMENT: Generated by write_TSPLIB (R package TSP)", "TYPE: TSP", paste("DIMENSION:", n_of_cities(x)), paste("EDGE_WEIGHT_TYPE:", type), file = zz, sep = "\n") ## fix row names rownames(x) <- NULL x <- do.call(data.frame, lapply(1:ncol(x), FUN = function(i) sprintf(paste("%0.", precision, "e", sep=""), x[,i]))) cat("NODE_COORD_SECTION", file = zz, sep = "\n") write.table(x, quote=FALSE, col.names = FALSE, file = zz) cat("EOF", file = zz, sep = "\n") close(zz) } TSP/R/tsp_concorde.R0000644000176200001440000001614413612366100013732 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## prepare distances as integers in the appropriate range [0..MAX] .prepare_dist_concorde <- function(x, MAX, precision) { ## handle inf x <- .replaceInf(x) ## fix neg. values min_x <- min(x) if(min_x<0) { warning("TSP contains negative distances. Shifting distances by subtracting the minimum.", immediate. = TRUE) x <- x - min_x } ## get max (excluding) to check for possible integer overflows max_x <- max(x) prec <- floor(log10(MAX / max_x)) x <- x * 10^prec if(prec < precision && any((x %% 1) != 0)) warning(paste0("Concorde/Linken can only handle distances represented as integers. Converting the provided distances to integers with precison ", prec, ". This may lead to rounding errors."), immediate. = TRUE) storage.mode(x) <- "integer" ## so write.TSBLIB does not do precision changes x } ## interface to the Concorde algorithm ## (can only handle TSP and no neg. distances!) tsp_concorde <- function(x, control = NULL){ if(!is.null(control$exe)) warning("exe is deprecated. Use concorde_path() instead!") ## get parameters control <- .get_parameters(control, list( clo = "", exe = .find_exe(control$exe, "concorde"), precision = 6, verbose = TRUE, keep_files = FALSE )) ## check x if(inherits(x, "TSP")){ if(n_of_cities(x) < 10) MAX <- 2^15 - 1 else MAX <- 2^31 - 1 x <- .prepare_dist_concorde(x, MAX, control$precision) }else if(inherits(x, "ETSP")) { ## nothing to do! }else stop("Concorde only handles TSP and ETSP.") ## get temp files and change working directory wd <- tempdir() dir <- getwd() setwd(wd) on.exit(setwd(dir)) ### fix for Windows by Stephen Eick ##temp_file <- tempfile(tmpdir = wd) temp_file <- basename(tempfile(tmpdir = wd)) ## file name needs to be unique tmp_file_in <- paste(temp_file, ".dat", sep = "") tmp_file_out <- paste(temp_file, ".sol", sep = "") ## precision is already handled! write_TSPLIB(x, file = tmp_file_in, precision = 0) ## change working directory ## do the call and read back result ## we do not check return values of concorde since they are not ## very consistent system2(control$exe, args = paste("-x", control$clo, "-o", tmp_file_out, tmp_file_in), stdout = if(control$verbose) "" else FALSE, stderr = if(control$verbose) "" else FALSE, ) if(!file.access(tmp_file_out) == 0) stop("Problems with reading Concorde's output.\nIs concorde properly installed?\nFor details see ? Concorde") ##else cat("Concorde done.\n") order <- scan(tmp_file_out, what = integer(0), quiet = TRUE) ## remove number of nodes and add one (result starts with 0) order <- order[-1] + 1L ## tidy up if(!control$keep_files) unlink(c(tmp_file_in, tmp_file_out)) else cat("File are in:", wd, "\n\n") order } ## interface to the Concorde's Chained Lin-Kernighan algorithm ## (can only handle TSP, handles neg. distances) tsp_linkern <- function(x, control = NULL){ if(!is.null(control$exe)) warning("exe is deprecated. Use concorde_path() instead!") ## get parameters control <- .get_parameters(control, list( exe = .find_exe(control$exe, "linkern"), clo = "", precision = 6, verbose = TRUE, keep_files = FALSE )) ## have to set -r for small instances <8 if(n_of_cities(x) <=8) control$clo <- paste(control$clo, "-k", n_of_cities(x)) ## check x if(inherits(x, "TSP")) { MAX <- 2^31 - 1 x <- .prepare_dist_concorde(x, MAX, control$precision) }else if(inherits(x, "ETSP")) { ## nothing to do } else stop("Linkern only works for TSP and ETSP.") ## get temp files wd <- tempdir() temp_file <- tempfile(tmpdir = wd) ## file name needs to be unique tmp_file_in <- paste(temp_file, ".dat", sep = "") tmp_file_out <- paste(temp_file, ".sol", sep = "") write_TSPLIB(x, file = tmp_file_in, precision = 0) ## change working directory dir <- getwd() setwd(wd) on.exit(setwd(dir)) ## do the call and read back result ## we do not check return values of concorde since they are not ## very consistent system2(control$exe, args = paste("-o", tmp_file_out, control$clo, tmp_file_in), stdout = if(control$verbose) "" else FALSE, stderr = if(control$verbose) "" else FALSE) if(!file.access(tmp_file_out) == 0) stop("Problems with reading linkern's output. Is linkern properly installed?") ##else cat("Concorde done.\n") order <- read.table(tmp_file_out)[,1] ## remove number of nodes and add one (result starts with 0) order <- order + as.integer(1) ## tidy up if(!control$keep_files) unlink(c(tmp_file_in, tmp_file_out)) else cat("File are in:", wd, "\n\n") order } ## get help page concorde_help <- function() { cat("The following options can be specified in solve_TSP with method \"concorde\" using clo in control:\n\n") system2(.find_exe(NULL, "concorde"), args = "") } linkern_help <- function() { cat("The following options can be specified in solve_TSP with method \"linkern\" using clo in control:\n\n") system2(.find_exe(NULL, "linkern"), args = "") } ## path concorde_path <- local({ .path <- NULL function(path){ if(missing(path)) { if(!is.null(.path)) return(.path) else { ## find concorde and/or linkern p <- dirname(Sys.which("concorde")) if(p == "") p <- dirname(Sys.which("linkern")) if(p == "") stop("Can not find executables for concorde or linkern. Please install the executables or set path manually.") return(p) } } else { if(!is.null(path)) { path <- normalizePath(path) ### translate all special characters ex <- c(list.files(path, pattern = "concorde", ignore.case = TRUE), list.files(path, pattern = "linkern", ignore.case = TRUE)) if(length(ex) < 1) stop(paste("no executable (concorde and/or linkern) found in", path)) cat("found:", ex, "\n") } .path <<- path invisible(.path) } } }) ## helper to find the concorde executable .find_exe <- function(exe = NULL, prog) { ## if not specified if(is.null(exe)) { ## was the path set ? if(!is.null(concorde_path())) exe <- paste(concorde_path(), .Platform$file.sep, prog, sep ="") ## no, so it must be in the systems execution path else exe <- prog } exe } TSP/R/insert_dummy.R0000644000176200001440000000365413612366100013771 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## insert a dummy city ##generic insert_dummy <- function(x, n = 1, const = 0, inf = Inf, label = "dummy") UseMethod("insert_dummy") ## use insert dummy from ATSP insert_dummy.TSP <- function(x, n = 1, const = 0, inf = Inf, label = "dummy") { x <- insert_dummy(ATSP(x), n, const, inf, label) TSP(x) } insert_dummy.ATSP <- function(x, n = 1, const = 0, inf = Inf, label = "dummy") { method <- attr(x, "method") n <- as.integer(n) p <- n_of_cities(x) if(length(label) == 1 && n > 1) label = rep(label, n) ## add dummy rows/columns x <- cbind(x, matrix(const, ncol = n, nrow = p, dimnames = list(NULL, label))) x <- rbind(x, matrix(const, ncol = p+n, nrow = n, dimnames = list(label, NULL))) ## place inf between dummies if(n>1) { x[(p+1):(p+n), (p+1):(p+n)] <- inf diag(x[(p+1):(p+n), (p+1):(p+n)]) <- 0 } attr(x, "method") <- method ATSP(x) } insert_dummy.ETSP <- function(x, n = 1, const = 0, inf = Inf, label = "dummy") stop("Dummy cities cannot be used with ETSP! Convert the problem into a TSP.") TSP/R/tour_length.R0000644000176200001440000000343413053151055013600 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## generic tour_length <- function(x, ...) UseMethod("tour_length") tour_length.TOUR <- function(x, tsp = NULL, ...) { if(is.null(tsp)) { len <- attr(x, "tour_length") if(is.null(len)) len <- NA return(len) } tour_length(x = tsp, order = x) } tour_length.TSP <- function(x, order, ...) { n <- n_of_cities(x) if(missing(order)) order <- 1:n .Call(R_tour_length_dist, x, order) } tour_length.ATSP <- function(x, order, ...) { n <- n_of_cities(x) if(missing(order)) order <- 1:n .Call(R_tour_length_matrix, x, order) } tour_length.ETSP <- function(x, order, ...) { n <- n_of_cities(x) if(n != nrow(x)) stop("x and order do not have the same number of cities!") if(missing(order)) order <- 1:n sum(sapply(1:(n-1), FUN = function(i) dist(x[order[i:(i+1)],]))) + as.numeric(dist(x[order[c(n,1)],])) } ### faster for small n but takes O(n^2) memory #tour_length.ETSP <- function(x, order) tour_length(as.TSP(x), order) TSP/R/tsp_insertion.R0000644000176200001440000001015313215316321014141 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## Insertion algorithms ## (Rosenkrantz et al. 1977) tsp_insertion <- function(x, type = "nearest", control = NULL){ ## since sample has an annoying convenience feature for ## lenght(x) == 1 choose1 <- function(x) if(length(x) > 1) sample(x, 1) else x ## this is slower than which.min and which.max but works also ## correctly for only values Inf in x and breaks ties randomly choose1_min <- function(x) choose1(which(x == min(x))) choose1_max <- function(x) choose1(which(x == max(x))) types <- c("nearest", "farthest", "cheapest", "arbitrary") type_num <- pmatch(type, types) if(is.na(type_num)) stop(paste("Unknown insertion type: ", sQuote(type))) ## x comes checked form solve_TSP/solve_ATSP n <- n_of_cities(x) ## we use a matrix for now (covers TSP and ATSP) asym <- inherits(x, "ATSP") x <- as.matrix(x) ## place first city control <- .get_parameters(control, list( start = sample(n, 1) )) start <- as.integer(control$start) if(start < 0 || start > n) stop(paste("illegal value for", sQuote("start"))) placed <- logical(n) placed[start] <- TRUE order <- c(start) ## place other cities while(any(placed == FALSE)) { ## find city to be inserted ks <- which(!placed) js <- which(placed) ## nearest / farthest if(type_num < 3) { m <- x[ks,js, drop = FALSE] ## for the asymmetric case we have to take distances ## from and to the city into account if(asym){ m <- cbind(m, t(x)[ks,js, drop = FALSE]) } ds <- sapply(1:length(ks), FUN = function(i) min(m[i, , drop = FALSE])) ## nearest/farthest insertion winner_index <- if(type_num == 1) choose1_min(ds) else choose1_max(ds) k <- ks[winner_index] } ## cheapest else if(type_num == 3) { winner_index <- choose1_min(sapply(ks, FUN = function(k) min(.Call(R_insertion_cost, x, order, k)) )) k <- ks[winner_index] ## we look for the optimal insertion place for k again later ## this is not necessary, but it is more convenient ## to reuse the code for the other insertion algorithms for now. } ## random else if(type_num == 4) k <- choose1(ks) ## just in case else stop("unknown insertion type") ## do insertion placed[k] <- TRUE if(length(order) == 1) order <- append(order, k) else { pos <- choose1_min(.Call(R_insertion_cost, x, order, k)) order <- append(order, k, after = pos) } } order } ### faster arbitrary insertion (random sampling takes care of breaking ties) tsp_insertion_arbitrary <- function(x, control = NULL){ ## x comes checked form solve_TSP/solve_ATSP n <- n_of_cities(x) control <- .get_parameters(control, list()) ## we use a matrix for now (covers TSP and ATSP) x <- as.matrix(x) ## deal with special cases if(nrow(x) == 1) return(1L) if(nrow(x) == 2) return(sample(1:2)) x[is.na(x)] <- Inf ## random order rorder <- sample(n) x <- x[rorder, rorder] ## FIXME: specify start city ## place first two cities order <- integer(n) order[1:2] <- 1:2 ## place other cities for(i in 3:n) { pos <- which.min(.Call(R_insertion_cost, x, order[1:(i-1L)], i)) + 1L order[((pos):i)+1L] <- order[(pos):i] order[pos] <- i } rorder[order] } TSP/R/solve_TSP.R0000644000176200001440000001166213514030555013131 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## generic solve_TSP <- function(x, method = NULL, control = NULL, ...) UseMethod("solve_TSP") ## TSP solve_TSP.TSP <- function(x, method = NULL, control = NULL, ...) { .solve_TSP(x, method, control, ...) } ## ATSP solve_TSP.ATSP <- function(x, method = NULL, control = NULL, as_TSP = FALSE, ...) { m <- pmatch(tolower(method), c("concorde", "linkern")) if(!as_TSP && !is.na(m) && length(m) > 0L) { warning("NOTE: Solver cannot solve the ATSP directly. Reformulating ATSP as TSP. Use 'as_TSP = TRUE' to supress this warning.\n") as_TSP <- TRUE } # reformulate ATSP as TSP if(as_TSP) { x_atsp <- x x <- reformulate_ATSP_as_TSP(x_atsp) } tour <- .solve_TSP(x, method, control, ...) if(as_TSP) { tour <- TOUR(tour[tour<=n_of_cities(x_atsp)], method = attr(tour, "method"), tsp = x_atsp) # Tour may be reversed tour_rev <- TOUR(rev(tour), method = attr(tour, "method"), tsp = x_atsp) if(tour_length(tour) > tour_length(tour_rev)) tour <- tour_rev } tour } ## ETSP solve_TSP.ETSP <- function(x, method = NULL, control = NULL, ...) { ## all but concorde and linkern can only do TSP m <- pmatch(tolower(method), c("concorde", "linkern")) if(length(m) == 0L || is.na(m)) x <- as.TSP(x) .solve_TSP(x, method, control, ...) } ## Deal with Inf: punish (-)Inf with max (min) +(-) 2*range .replaceInf <- function(x, pInf = NULL, nInf = NULL) { if(any(is.infinite(x))) { range_x <- range(x, na.rm = TRUE, finite = TRUE) if(is.null(pInf)) pInf <- range_x[2] + 2* diff(range_x) if(is.null(nInf)) nInf <- range_x[1] - 2* diff(range_x) x[x == Inf] <- pInf x[x == -Inf] <- nInf } x } ## workhorse .solve_TSP <- function(x, method = NULL, control = NULL, ...) { ## add ... to control control <- c(control, list(...)) ## methods methods <- c( "identity", "random", "nearest_insertion", "farthest_insertion", "cheapest_insertion", "arbitrary_insertion", "nn", "repetitive_nn", "2-opt", ### deprecated "two_opt", "concorde", "linkern" ) ## default is arbitrary_insertion + two_opt if(is.null(method)) { method <- "arbitrary_insertion" if(is.null(control$two_opt)) control <- c(control, list(two_opt = TRUE)) } else method <- match.arg(tolower(method), methods) ## check for NAs if(any(is.na(x))) stop("NAs not allowed!") ## Inf x_ <- .replaceInf(x) ## work horses .solve_TSP_worker <- function(x_, method, control) { order <- switch(method, identity = seq(n_of_cities(x_)), random = sample(n_of_cities(x_)), nearest_insertion = tsp_insertion(x_, type = "nearest", control = control), farthest_insertion = tsp_insertion(x_, type = "farthest", control = control), cheapest_insertion = tsp_insertion(x_, type = "cheapest", control = control), # arbitrary_insertion = tsp_insertion(x_, type = "arbitrary", control = control), arbitrary_insertion = tsp_insertion_arbitrary(x_, control = control), nn = tsp_nn(x_, control = control), repetitive_nn = tsp_repetitive_nn(x_, control = control), two_opt = tsp_two_opt(x_, control = control), '2-opt' = tsp_two_opt(x_, control = control), concorde = tsp_concorde(x_, control = control), linkern = tsp_linkern(x_, control = control) ) ### do refinement two_opt if(!is.null(control$two_opt) && control$two_opt) { order <- tsp_two_opt(x_, control = c(control, list(tour = order))) method <- paste(method , "+two_opt", sep = "") } TOUR(order, method=method, tsp=x) } ## do rep? if(!is.null(control$rep)) n <- control$rep else n <- 1L if(method == "concorde" || method == "linkern") { n <- 1L control$two_opt <- NULL ## no two_opt for these! } if(method == "repetitive_nn") n <- 1L if(n==1L) return(.solve_TSP_worker(x_, method, control)) #l <- replicate(n, .solve_TSP_worker(x_, method, control), simplify = FALSE) l <- foreach(i = 1:n) %dopar% .solve_TSP_worker(x_, method, control) l <- l[[which.min(sapply(l, attr, "tour_length"))]] attr(l, "method") <- paste(attr(l, "method"), "_rep_", n, sep="") return(l) } TSP/R/ETSP.R0000644000176200001440000000414412606077054012031 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## create a Euclidean TSP problem ETSP <- function(x, labels = NULL) { if(inherits(x, "ETSP")) return(x) x <- as.ETSP(x) if(!is.null(labels)) rownames(x) <- labels x } ## coercion as.ETSP <- function(x) UseMethod("as.ETSP") as.ETSP.matrix <- function(x){ mode(x) <- "numeric" if(is.null(rownames(x))) rownames(x) <- 1:nrow(x) class(x) <- c("ETSP", class(x)) x } as.ETSP.data.frame <- function(x){ as.ETSP(as.matrix(x)) } as.TSP.ETSP <- function(x) TSP(dist(x)) as.matrix.ETSP <- function(x, ...) { unclass(x) } ## print print.ETSP <- function(x, ...) { cat("object of class", sQuote(class(x)[1]), "\n") cat(n_of_cities(x), "cities", "(Euclidean TSP)\n") } ## number of cities n_of_cities.ETSP <- function(x) nrow(x) ## labels labels.ETSP <- function(object, ...) rownames(object) ## image image.ETSP <- function(x, order, col = gray.colors(64), ...) { p <- n_of_cities(x) if(missing(order)) order <- 1:p x <- as.TSP(x) graphics::image.default(1:p, 1:p, as.matrix(x)[order, order], col = col, ...) } plot.ETSP <- function(x, y = NULL, tour = NULL, tour_lty = 2, tour_col = 1,...) { x <- as.matrix(x) plot(x, y = NULL, ...) if(!is.null(y)) tour <- TOUR(y) if(!is.null(tour)) polygon(x[tour,], lty = tour_lty, border = tour_col) } TSP/R/TOUR.R0000644000176200001440000000366412606077054012055 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. TOUR <- function(x, method=NA, tsp=NULL){ if(inherits(x, "TOUR")) return(x) x <- as.TOUR(x) attr(x, "method") <- as.character(method) if(!is.null(tsp)){ attr(x, "tour_length") <- tour_length(x, tsp) names(x) <- labels(tsp)[x] } x } ## coercion as.TOUR <- function(object) UseMethod("as.TOUR") as.TOUR.numeric <- function(object){ l <- labels(object) ### preserve lables object <- as.integer(object) names(object) <- l as.TOUR(object) } as.TOUR.integer <- function(object){ ## check tour if(any(object < 1) || any(object > length(object)) || any(is.na(object))) stop("tour contains illegal elements.") if(any(duplicated(object))) stop("tour indices are not unique.") class(object) <- c("TOUR", class(object)) object } ## helper for tour print.TOUR <- function(x, ...){ cat("object of class", sQuote(class(x)[1]), "\n") cat("result of method", sQuote(attr(x, "method")), "for", length(x), "cities\n") if(!is.null(attr(x, "tour_length"))) cat("tour length:", attr(x, "tour_length"), "\n") else cat("tour length: unknown\n") } TSP/R/TSP.R0000644000176200001440000000552013513342076011720 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## create a TSP problem TSP <- function(x, labels = NULL, method = NULL) { if(inherits(x, "TSP")) return(x) x <- as.TSP(x) if(!is.null(labels)) attr(x, "Labels") <- labels if(!is.null(method)) attr(x, "method") <- method x } ## coercion as.TSP <- function(x) UseMethod("as.TSP") as.TSP.dist <- function(x){ ## make sure we have a upper triangle matrix w/o diagonal x <- as.dist(x, diag = FALSE, upper = FALSE) ## make sure we have labels if(is.null(attr(x, "Labels"))) attr(x, "Labels") <- c(1:n_of_cities(x)) if(any(is.nan(x))) stop(paste(sQuote("NAs"), "not supported")) ## make sure data is numeric mode(x) <- "numeric" class(x) <- c("TSP", class(x)) x } as.TSP.matrix <- function(x){ if(!isSymmetric(x)) stop("TSP requires a symmetric matrix") method <- attr(x, "method") x <- as.dist(x, diag = FALSE, upper = FALSE) attr(x, "method") <- method ## make sure we have labels if(is.null(attr(x, "Labels"))) attr(x, "Labels") <- c(1:n_of_cities(x)) if(any(is.nan(x))) stop(paste(sQuote("NAs"), "not supported")) ## make sure data is numeric mode(x) <- "numeric" class(x) <- c("TSP", class(x)) x } as.dist.TSP <- function(m, ...) { class(m) <- "dist" as.dist(m, ...) } ## print print.TSP <- function(x, ...) { method <- attr(x, "method") if(is.null(method)) method <- "unknown" cat("object of class", sQuote(class(x)[1]), "\n") cat(n_of_cities(x), "cities", paste("(distance ", sQuote(method),")", sep=""), "\n") } ## number of cities n_of_cities.TSP <- function(x) attr(x, "Size") ## generic for n_of_cities n_of_cities <- function(x) UseMethod("n_of_cities") n_of_cities.default <- n_of_cities.TSP ## labels labels.TSP <- function(object, ...) attr(object, "Labels") ## image image.TSP <- function(x, order, col = gray.colors(64), ...) { p <- n_of_cities(x) if(missing(order)) order <- 1:p graphics::image.default(1:p, 1:p, as.matrix(x)[order, order], col = col, ...) } TSP/R/read_TSPLIB.R0000644000176200001440000001115513471325021013235 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## read a simple TSPLIB format file read_TSPLIB <- function(file, precision = 0) { ## TSP or ATSP type <- NULL lines <- readLines(file) ## get info metadata <- grep(":", lines) info <- list() lapply(strsplit(lines[metadata], "[[:space:]]*:[[:space:]]*"), FUN = function(x) { x[2] <- sub("[[:space:]]*$","",x[2]) ## kill trailing spaces info[[toupper(x[1])]] <<- toupper(x[2]) }) ## check if(substr(info$TYPE, 1, 3) == "TSP") type <- "TSP" else if(substr(info$TYPE, 1, 3) == "ATS") type <- "ATSP" else stop ("Currently the only implemented TYPEs are TSP and ATS(P)!") dim <- as.integer(info$DIMENSION) if(info$EDGE_WEIGHT_TYPE == "EXPLICIT") { ## get data data_start <- grep("EDGE_WEIGHT_SECTION", lines, ignore.case = TRUE) if(length(data_start) == 0) stop("EDGE_WEIGHT_SECTION missing") data <- lines[(data_start+1):length(lines)] data <- sub("EOF", "", data, ignore.case = TRUE) ## kill optional EOF data <- sub("^[[:space:]]*", "", data)## kill leading spaces data <- strsplit(paste(data, collapse = " "), "[[:space:]]+")[[1]] ## remove everything after the data if(info$EDGE_WEIGHT_FORMAT == "FULL_MATRIX") data <- data[1:(dim^2)] else if(info$EDGE_WEIGHT_FORMAT == "UPPER_ROW" || info$EDGE_WEIGHT_FORMAT == "LOWER_COL" || info$EDGE_WEIGHT_FORMAT == "UPPER_COL" || info$EDGE_WEIGHT_FORMAT == "LOWER_ROW") data <- data[1:(dim*(dim-1)/2)] else if(info$EDGE_WEIGHT_FORMAT == "UPPER_DIAG_ROW" || info$EDGE_WEIGHT_FORMAT == "LOWER_DIAG_COL" || info$EDGE_WEIGHT_FORMAT == "UPPER_DIAG_COL" || info$EDGE_WEIGHT_FORMAT == "LOWER_DIAG_ROW") data <- data[1:(dim*(dim-1)/2 + dim)] data <- as.numeric(data) if(precision != 0) data <- data / 10^precision ## ATSP if(type == "ATSP") { if(info$EDGE_WEIGHT_FORMAT == "FULL_MATRIX"){ ## todo: find out if FULL_MATRIX is row or column oriented? data <- matrix(data, ncol = dim) }else stop("ATSP needs EDGE_WEIGHT_FORMAT FULL_MATRIX!") return(ATSP(data)) } ## TSP ## we have only symmetric data here! if(info$EDGE_WEIGHT_FORMAT == "FULL_MATRIX") { data <- as.dist(matrix(data, ncol = dim)) }else if(info$EDGE_WEIGHT_FORMAT == "UPPER_ROW" || info$EDGE_WEIGHT_FORMAT == "LOWER_COL") { class(data) <- "dist" attr(data, "Size") <- dim attr(data, "Diag") <- FALSE attr(data, "Upper") <- FALSE }else if(info$EDGE_WEIGHT_FORMAT == "UPPER_COL" || info$EDGE_WEIGHT_FORMAT == "LOWER_ROW") { m <- matrix(NA, nrow = dim, ncol = dim) m[upper.tri(m, diag = FALSE)] <- data data <- as.dist(t(m)) }else if(info$EDGE_WEIGHT_FORMAT == "UPPER_DIAG_ROW" || info$EDGE_WEIGHT_FORMAT == "LOWER_DIAG_COL") { class(data) <- "dist" attr(data, "Size") <- dim attr(data, "Diag") <- TRUE attr(data, "Upper") <- FALSE data <- as.dist(data, diag = FALSE) }else if(info$EDGE_WEIGHT_FORMAT == "UPPER_DIAG_COL" || info$EDGE_WEIGHT_FORMAT == "LOWER_DIAG_ROW") { m <- matrix(NA, nrow = dim, ncol = dim) m[upper.tri(m, diag = TRUE)] <- data data <- as.dist(t(m)) }else stop("The specified EDGE_WEIGHT_FORMAT is not implemented!") return(TSP(data)) } else if (info$EDGE_WEIGHT_TYPE == "EUC_2D" || info$EDGE_WEIGHT_TYPE == "EUC_2D") { data_start <- grep("NODE_COORD_SECTION", lines, ignore.case = TRUE) if(length(data_start) == 0) stop("NODE_COORD_SECTION missing") data <- lines[(data_start+1):(data_start+dim)] data <- matrix(as.numeric(unlist(strsplit(data, split="\\s+"))), nrow = dim, byrow = TRUE) data <- data[,-1] return(ETSP(data)) } stop("EDGE_WEIGHT_TYPE not implemented! Implemented types are EXPLICIT, EUC_2D and EUC_3D") } TSP/R/cut_tour.R0000644000176200001440000000352613612366100013114 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. cut_tour.TOUR <- function(x, cut, exclude_cut = TRUE) { ## city label if(is.character(cut)) { cut <- which(as.logical(apply(sapply(cut, "==", labels(x)), MARGIN = 1, sum))) if(length(cut)<1) stop("cut has to exist") ## city id } else { if(any(is.na(cut <- match(cut, x)))) stop("cut has to exist") } if(length(cut) == 1L) { ## single path path <- c(x,x)[(cut + as.numeric(exclude_cut)):(length(x) + cut - 1L)] } else { ## multiple paths, return as a list path_names <- labels(x)[cut] ## make first cut the begining. Note we keeb the boundary at the begining and the end! path <- c(x,x)[cut[1]:(length(x) + cut[1])] cut2 <- c(cut - cut[1] + 1L, length(x)) path <- lapply(2:length(cut2), FUN = function(i) path[(cut2[i-1L] + as.numeric(exclude_cut)):(cut2[i]-1L)]) names(path) <- path_names } path } ##generic cut_tour <- function(x, cut, exclude_cut = TRUE) UseMethod("cut_tour") TSP/R/tsp_nn.R0000644000176200001440000000446012662161447012562 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## nearest neighbor algorithm tsp_nn <- function(x, control = NULL) { ## parameter x comes checked from solve_TSP/solve_ATSP n <- n_of_cities(x) ## we use a matrix for now (coveres TSP and ATSP) x <- as.matrix(x) control <- .get_parameters(control, list( start = sample(n, 1) )) start <- control$start if(start < 0 || start > n) stop(paste("illegal value for", sQuote("start"))) placed <- logical(n) order <- integer(n) ## place first city current <- start order[1L] <- current placed[current] <- TRUE while(length(rest <- which(!placed)) > 0L) { ## nearest <- rest[which.min(x[current,rest])] ## which.min has problems with Inf ## so we can break ties randomly now too x_sub <- x[current, rest] current <- rest[which(x_sub == min(x_sub, na.rm = TRUE))] if(length(current) > 1L) current <- sample(current, 1) ## place city order[n + 1L - length(rest)] <- current placed[current] <- TRUE } order } ## repetitive NN tsp_repetitive_nn <- function(x, control){ n <- n_of_cities(x) #tours <- lapply(1:n, function(i) tsp_nn(x, control = list(start = i))) ## no backend would warn! i <- 0L ## for R CMD check (no global binding for i) suppressWarnings( tours <- foreach(i = 1:n) %dopar% tsp_nn(x, control = list(start = i)) ) lengths <- sapply(tours, FUN = function(i) tour_length(x, i)) tours[[which.min(lengths)]] } TSP/R/ATSP.R0000644000176200001440000000520113373424542012020 0ustar liggesusers####################################################################### # TSP - Traveling Salesperson Problem # Copyrigth (C) 2011 Michael Hahsler and Kurt Hornik # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## create a (asymmetric) ATSP problem ATSP <- function(x, labels = NULL, method = NULL) { if(inherits(x, "ATSP")) return(x) atsp <- as.ATSP(x) if(!is.null(labels)) dimnames(atsp) <- list(labels, labels) if(!is.null(method)) attr(atsp, "method") <- method atsp } as.ATSP <- function(x) UseMethod("as.ATSP") as.ATSP.matrix <- function(x){ .isSquare <- function(x) (dim(x)[1] == dim(x)[2]) if(!.isSquare(x)) stop("ATSP requires a square matrix") ## check for NAs if(any(is.nan(x))) stop(paste(sQuote("NAs"), "not supported")) ## make sure we have labels if(is.null(dimnames(x))) dimnames(x) <- list(1:dim(x)[1], 1: dim(x)[1]) if(is.null(colnames(x))) colnames(x) <- rownames(x) if(is.null(rownames(x))) rownames(x) <- colnames(x) ## make sure data is numeric mode(x) <- "numeric" class(x) <- c("ATSP", class(x)) x } as.ATSP.dist <- function(x){ method <- attr(x, "method") x <- as.ATSP(as.matrix(x)) ## make sure data is numeric mode(x) <- "numeric" class(x) <- c("ATSP", class(x)) attr(x, "method") <- method x } ## print print.ATSP <- function(x, ...) { method <- attr(x, "method") if(is.null(method)) method <- "unknown" cat("object of class", sQuote(class(x)[1]), " (asymmetric TSP) \n") cat(n_of_cities(x), "cities", paste("(distance ", sQuote(method),")", sep=""), "\n") } ## number of cities n_of_cities.ATSP <- function(x) nrow(x) ## labels labels.ATSP <- function(object, ...) dimnames(object)[[1]] ## image image.ATSP <- function(x, order, col = gray.colors(64), ...) { p <- n_of_cities(x) if(missing(order)) order <- 1:p graphics::image.default(1:p, 1:p, x[order, order], col = col, ...) } ## coerce to matrix as.matrix.ATSP <- function(x, ...){ unclass(x) } TSP/R/AAAparameter.R0000644000176200001440000000405513612366100013531 0ustar liggesusers####################################################################### # Code to check parameter/control objects # Copyrigth (C) 2011-2016 Michael Hahsler # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License along # with this program; if not, write to the Free Software Foundation, Inc., # 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. ## helper to parse parameter lists with defaults .nodots <- function(...) { l <- list(...) if(length(l) > 0L) warning("Unknown arguments: ", paste(names(l), "=",l, collapse=", ")) } .get_parameters <- function(parameter, defaults) { defaults <- as.list(defaults) parameter <- as.list(parameter) ## add verbose if(is.null(defaults$verbose)) defaults$verbose <- FALSE if(length(parameter) != 0) { o <- pmatch(names(parameter), names(defaults)) ## unknown parameter # if(any(is.na(o))){ # warning(sprintf(ngettext(length(is.na(o)), # "Unknown parameter: %s", # "Unknown parameters: %s"), # paste(names(parameter)[is.na(o)], # collapse = ", ")), call. = FALSE, immediate. = TRUE) # # cat("Available parameter (with default values):\n") # #print(defaults) # cat(rbind(names(defaults)," = ", gsub("\n"," ",as.character(defaults))), # sep=c("\t"," ","\n")) # } defaults[o[!is.na(o)]] <- parameter[!is.na(o)] } if(defaults$verbose) { cat("Used control parameters:\n") #print(defaults) cat(rbind(names(defaults)," = ", strtrim(gsub("\n"," ",as.character(defaults)), 50)), sep=c("\t"," ","\n")) } defaults } TSP/NEWS.md0000644000176200001440000000575513623556657012054 0ustar liggesusers# TSP 1.1-9 (02/02/2020) * Maintenance release. # TSP 1.1-8 (01/23/2020) ## New Feature * solve_TSP for ATSP gained parameter as_TSP to solve the ATSP reformulated as a TSP. * Concorde and linkern can now solve ATSP using a reformulation as a TSP. * cut_tour can now cut a tour into multiple paths. # TSP 1.1-7 (05/22/2019) ## Bugfixes * concorde_path now normalizes the path (translates . and ~). * reformulate_ATSP_as_TSP now keeps the method attribute (i.e., used distance measure) * TSP and ATSP gained parameter method to store the name of the used distance metric. * Fixed read_TSPLIB for EDGE_WEIGHT_FORMAT of LOWER_ROW, LOWER_DIAG_ROW, UPPER_COL and UPPER_DIAG_COL (reported by klukac). # TSP 1.1-6 (04/29/2018) ## Bugfixes * Start for insertion algorithms is now coerced to integer. * Fixed problem with TSP with 1 city on Win 32 on R 3.5.0. # TSP 1.1-5 (02/21/2017) * fixed TSP labels. * fixed tour_length for ETSP and added tests. # TSP 1.1-4 (2/21/2016) * fixed bug in arbitrary insertion for TSPs with two or less cities (bug report by Shrinidhee Shevade). * concorde and linkern help: exe argument was removed. The exe control argument for both methods in solve_TSP is now deprecated. Use concorde_path(path) instead. * concorde and linkern gained a control argument verbose to suppress the output. # TSP 1.1-3 (9/2/2015) * two-opt now works correctly with asymmetric TSPs (bug report by Luis Martinez). # TSP 1.1-2 (7/30/2015) * Fixed imports for non-base packages. # TSP 1.1-1 (5/15/2015) * improved speed of C code. * compatibility with new release of testthat # TSP 1.1-0 (3/14/2015) * default method is now arbitrary_insertion with two_opt refinement. * we use foreach (use doParallel) to compute repetitions in parallel * ETSP (Euclidean TSP) added. * generic and arguments for tour_lengh have # Changed (fist argument is now a tour). * method "2-opt" was renamed to "two_opt" so it can also be used as a proper variable name. * solve_TSP gained methods "identity" and "random". * solve_TSP gained options "repetition" and "two_opt". # TSP 1.0-10 (2/3/2015) * added check for argument cut in cut_tour * Finding concord and linkern is now case insensitive (Reported by Mark Otto) # TSP 1.0-9 (7/16/2014) * Check for NAs in distances. * +INF and -INF are now handled in solve_TSP. * fixed single quotes in vignette. # TSP 1.0-8 (9/6/2013) * service release. # TSP 1.0-7 (8/22/2012) * Added PACKAGE argument to C calls. # TSP 1.0-6 (11/29/2011) * Fixed bug in read_TSPLIB. # TSP 1.0-5 (11/10/2011) * Changed constructor for TOUR to allow for method and tour_length. * Bugfix: labels in creator ATSP() (reported by Tiffany Chen) # TSP 1.0-4 (8/31/2011) * Fixed bug with missing row/column labels in as.ATSP() (reported by Ian Deters) # TSP 1.0-3 (5/26/2011) * Service release # TSP 1.0-2 (1/14/2011) * Fixed Windows/R bug with temp files. * Fixed the code for SpatialLines thanks to Roger Bivand. # TSP 0.1-2 (9/18/2006) * Initial release. 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TSP/inst/0000755000176200001440000000000013623557437011714 5ustar liggesusersTSP/inst/examples/0000755000176200001440000000000012606077054013522 5ustar liggesusersTSP/inst/examples/d493.tsp0000644000176200001440000003277512606077054014753 0ustar liggesusersNAME : d493 COMMENT : Drilling problem (Reinelt) TYPE : TSP DIMENSION : 493 EDGE_WEIGHT_TYPE : EUC_2D NODE_COORD_SECTION 1 0.00000e+00 0.00000e+00 2 1.11630e+03 1.55520e+03 3 1.35760e+03 1.47900e+03 4 1.14810e+03 1.77110e+03 5 1.18620e+03 1.79650e+03 6 1.20520e+03 1.88540e+03 7 1.23700e+03 1.99340e+03 8 1.30050e+03 2.00610e+03 9 1.16080e+03 2.02510e+03 10 1.17350e+03 2.03780e+03 11 1.22430e+03 2.05050e+03 12 1.35130e+03 2.24100e+03 13 1.73230e+03 2.13310e+03 14 1.74500e+03 2.19020e+03 15 1.76400e+03 2.29180e+03 16 1.76400e+03 2.34260e+03 17 1.73230e+03 2.39340e+03 18 1.74500e+03 2.41880e+03 19 1.64970e+03 2.43150e+03 20 1.75770e+03 2.52040e+03 21 2.29740e+03 1.77110e+03 22 2.21490e+03 1.42820e+03 23 2.22760e+03 1.33930e+03 24 2.18310e+03 1.32030e+03 25 2.61490e+03 1.11070e+03 26 2.50700e+03 1.16150e+03 27 2.34820e+03 9.52000e+02 28 2.22120e+03 1.00910e+03 29 2.20850e+03 1.08530e+03 30 2.20220e+03 1.13610e+03 31 2.21490e+03 1.17420e+03 32 2.02440e+03 1.12340e+03 33 2.04340e+03 1.30120e+03 34 1.94820e+03 1.30760e+03 35 1.94180e+03 1.39010e+03 36 1.84660e+03 1.41550e+03 37 1.75770e+03 1.36470e+03 38 1.80210e+03 1.35200e+03 39 1.83390e+03 1.26310e+03 40 1.73230e+03 1.25040e+03 41 2.04340e+03 1.58060e+03 42 2.04980e+03 1.74570e+03 43 1.99900e+03 1.80290e+03 44 1.96090e+03 1.81560e+03 45 2.05610e+03 1.82190e+03 46 2.01170e+03 1.82830e+03 47 2.04340e+03 1.85370e+03 48 1.84660e+03 1.78380e+03 49 1.82120e+03 1.82830e+03 50 1.84660e+03 1.86640e+03 51 1.81480e+03 1.65050e+03 52 1.66880e+03 1.80920e+03 53 1.85930e+03 2.16480e+03 54 1.98630e+03 2.13310e+03 55 2.01170e+03 2.17750e+03 56 1.94820e+03 2.19660e+03 57 1.89100e+03 2.24740e+03 58 2.01170e+03 2.27280e+03 59 2.03710e+03 2.30450e+03 60 2.05610e+03 2.35530e+03 61 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2.59590e+03 2.77440e+03 99 2.50700e+03 2.77440e+03 100 2.72290e+03 2.75540e+03 101 2.61490e+03 2.74900e+03 102 2.88800e+03 2.73000e+03 103 3.21180e+03 2.73000e+03 104 3.14200e+03 2.71730e+03 105 2.75460e+03 2.69820e+03 106 2.45620e+03 2.69820e+03 107 2.57050e+03 2.62200e+03 108 2.72290e+03 2.62200e+03 109 3.36420e+03 2.62200e+03 110 2.90070e+03 2.61570e+03 111 3.13560e+03 2.60300e+03 112 2.71020e+03 2.59660e+03 113 2.71650e+03 2.54580e+03 114 2.88800e+03 2.53310e+03 115 2.84990e+03 2.51410e+03 116 2.29740e+03 2.51410e+03 117 2.60860e+03 2.49500e+03 118 3.22450e+03 2.48870e+03 119 2.69110e+03 2.47600e+03 120 2.87530e+03 2.43790e+03 121 2.50060e+03 2.41880e+03 122 2.43080e+03 2.39980e+03 123 2.87530e+03 2.39980e+03 124 3.12930e+03 2.36800e+03 125 2.58320e+03 2.36800e+03 126 2.49430e+03 2.36800e+03 127 2.78000e+03 2.36170e+03 128 2.33550e+03 2.35530e+03 129 2.61490e+03 2.31720e+03 130 2.92610e+03 2.30450e+03 131 2.80540e+03 2.29180e+03 132 2.58320e+03 2.29180e+03 133 2.82450e+03 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1.15520e+03 489 3.40870e+03 1.16150e+03 490 3.47220e+03 1.17420e+03 491 3.69440e+03 1.30120e+03 492 3.74520e+03 1.27580e+03 493 3.74520e+03 1.02180e+03 EOF TSP/inst/doc/0000755000176200001440000000000013623557437012461 5ustar liggesusersTSP/inst/doc/TSP.Rnw0000644000176200001440000013174513623555613013624 0ustar liggesusers%\documentclass[10pt,a4paper,fleqn]{article} \documentclass[nojss]{jss} \usepackage[english]{babel} %% my packages %\usepackage{a4wide} %\usepackage[round,longnamesfirst]{natbib} %\usepackage{hyperref} % \usepackage{amsmath} \usepackage{amsfonts} % %\newcommand{\strong}[1]{{\normalfont\fontseries{b}\selectfont #1}} \newcommand{\class}[1]{\mbox{\textsf{#1}}} \newcommand{\func}[1]{\mbox{\texttt{#1()}}} %\newcommand{\code}[1]{\mbox{\texttt{#1}}} %\newcommand{\pkg}[1]{\strong{#1}} \newcommand{\samp}[1]{`\mbox{\texttt{#1}}'} %\newcommand{\proglang}[1]{\textsf{#1}} \newcommand{\set}[1]{\mathcal{#1}} %\usepackage{Sweave} %% \VignetteIndexEntry{Introduction to TSP} \author{Michael Hahsler\\Southern Methodist University \And Kurt Hornik\\Wirtschaftsuniversit\"at Wien} \title{\pkg{TSP} -- Infrastructure for the Traveling Salesperson Problem} %% for pretty printing and a nice hypersummary also set: \Plainauthor{Michael Hahsler, Kurt Hornik} %% comma-separated \Plaintitle{TSP -- Infrastructure for the Traveling Salesperson Problem} %% without formatting \Shorttitle{Infrastructure for the TSP} %% a short title (if necessary) %% an abstract and keywords \Abstract{ The traveling salesperson problem (also known as traveling salesman problem or TSP) is a well known and important combinatorial optimization problem. The goal is to find the shortest tour that visits each city in a given list exactly once and then returns to the starting city. Despite this simple problem statement, solving the TSP is difficult since it belongs to the class of NP-complete problems. The importance of the TSP arises besides from its theoretical appeal from the variety of its applications. Typical applications in operations research include vehicle routing, computer wiring, cutting wallpaper and job sequencing. The main application in statistics is combinatorial data analysis, e.g., reordering rows and columns of data matrices or identifying clusters. In this paper we introduce the \proglang{R}~package \pkg{TSP} which provides a basic infrastructure for handling and solving the traveling salesperson problem. The package features S3 classes for specifying a TSP and its (possibly optimal) solution as well as several heuristics to find good solutions. In addition, it provides an interface to \emph{Concorde}, one of the best exact TSP solvers currently available. } \Keywords{combinatorial optimization, traveling salesman problem, \proglang{R}} \Plainkeywords{combinatorial optimization, traveling salesman problem, R} %% without formatting %% The address of (at least) one author should be given %% in the following format: \Address{ Michael Hahsler\\ Engineering Management, Information, and Systems\\ Lyle School of Engineering\\ Southern Methodist University\\ P.O. Box 750123 \\ Dallas, TX 75275-0123\\ E-mail: \email{mhahsler@lyle.smu.edu}\\ Kurt Hornik\\ Department of Finance, Accounting and Statistics\\ Wirtschaftsuniversit\"at Wien\\ 1090 Wien, Austria\\ E-mail: \email{kurt.hornik@wu-wien.ac.at}\\ URL: \url{http://statmath.wu.ac.at/~hornik/} } \begin{document} <>= options(width = 75, useFancyQuotes=FALSE, prompt="R> ") ### for sampling set.seed(1234) @ %\title{Introduction to \pkg{TSP} -- Infrastructure for the Traveling % Salesperson Problem} %\author{Michael Hahsler and Kurt Hornik} \maketitle \sloppy %\abstract{ % The traveling salesperson (or, salesman) problem (TSP) is a % well known and important combinatorial optimization problem. The goal % is to find the shortest tour that visits each city in a given list % exactly once and then returns to the starting city. Despite this % simple problem statement, solving the TSP is difficult since it % belongs to the class of NP-complete problems. The importance of the % TSP arises besides from its theoretical appeal from the variety of its % applications. Typical applications in operations research include % vehicle routing, computer wiring, cutting wallpaper and job % sequencing. The main application in statistics is combinatorial data % analysis, e.g., reordering rows and columns of data matrices or % identifying clusters. In this paper we introduce the % \proglang{R}~package \pkg{TSP} which provides a basic infrastructure % for handling and solving the traveling salesperson problem. The % package features S3 classes for specifying a TSP and its (possibly % optimal) solution as well as several heuristics to find good % solutions. In addition, it provides an interface to \emph{Concorde}, % one of the best exact TSP solvers currently available. } \section{Introduction} The traveling salesperson problem~\citep[TSP;][]{Lawler1985, Gutin2002} is a well known and important combinatorial optimization problem. The goal is to find the shortest tour that visits each city in a given list exactly once and then returns to the starting city. Formally, the TSP can be stated as follows. The distances between $n$ cities are stored in a distance matrix $\mathbf{D}$ with elements $d_{ij}$ where $i,j = 1\dots n$ and the diagonal elements $d_{ii}$ are zero. A \emph{tour} can be represented by a cyclic permutation $\pi$ of $\{1, 2,\dots, n\}$ where $\pi(i)$ represents the city that follows city $i$ on the tour. The traveling salesperson problem is then the optimization problem to find a permutation $\pi$ that minimizes the \emph{length of the tour} denoted by \begin{equation} \sum_{i=1}^n d_{i\pi(i)}. \end{equation} % see Lenstra & Kan 1975: Some simple Applications to the TSP For this minimization task, the tour length of $(n-1)!$ permutation vectors have to be compared. This results in a problem which is very hard to solve and in fact known to be NP-complete~\citep{Johnson1985a}. However, solving TSPs is an important part of applications in many areas including vehicle routing, computer wiring, machine sequencing and scheduling, frequency assignment in communication networks~\citep{Lenstra1975, Punnen2002}. %and structuring of %matrices~\citep{Lenstra1975, Punnen2002}. Applications in statistical data analysis include ordering and clustering objects. For example, data analysis applications in psychology ranging from profile smoothing to finding an order in developmental data are presented by~\cite{Hubert1978}. Clustering and ordering using TSP solvers is currently becoming popular in biostatistics. For example, \cite{Ray2007} describe an application for ordering genes and \cite{Johnson2006} use a TSP solver for clustering proteins. In this paper we give a very brief overview of the TSP and introduce the \proglang{R}~package \pkg{TSP} which provides an infrastructure for handling and solving TSPs. The paper is organized as follows. In Section~\ref{sec:TSP} we briefly present important aspects of the TSP including different problem formulations and approaches to solve TSPs. In Section~\ref{sec:infrastructure} we give an overview of the infrastructure implemented in \pkg{TSP} and the basic usage. In Section~\ref{sec:examples}, several examples are used to illustrate the package's capabilities. Section~\ref{sec:conclusion} concludes the paper. A previous version of this manuscript was published in the \emph{Journal of Statistical Software} \citep{TSP:Hahsler+Hornik2007}. \section{Theory} \label{sec:TSP} In this section, we briefly summarize some aspects of the TSP which are important for the implementation of the \pkg{TSP} package described in this paper. For a complete treatment of all aspects of the TSP, we refer the interested reader to the classic book edited by \cite{Lawler1985} and the more modern book edited by \cite{Gutin2002}. It has to be noted that in this paper, following the origin of the TSP, the term \emph{distance} is used. Distance is used here interchangeably with dissimilarity or cost and, unless explicitly stated, no restrictions to measures which obey the triangle inequality are made. An important distinction can be made between the symmetric TSP and the more general asymmetric TSP. For the symmetric case (normally referred to as just \emph{TSP}), for all distances in $\mathbf{D}$ the equality $d_{ij} = d_{ji}$ holds, i.e., it does not matter if we travel from $i$ to $j$ or the other way round, the distance is the same. In the asymmetric case (called \emph{ATSP}), the distances are not equal for all pairs of cities. Problems of this kind arise when we do not deal with spatial distances between cities but, e.g., with the cost or necessary time associated with traveling between locations, where the price for the plane ticket between two cities may be different depending on which way we go. \subsection{Different formulations of the TSP} \label{sec:formulations} Other than the permutation problem in the introduction, the TSP can also be formulated as a graph theoretic problem. Here the TSP is formulated by means of a complete graph $G = (V, E)$, where the cities correspond to the node set $V = \{1,2,\ldots,n\}$ and each edge $e_i \in E$ has an associated weight $w_i$ representing the distance between the nodes it connects. If the graph is not complete, the missing edges can be replaced by edges with very large distances. The goal is to find a \emph{Hamiltonian cycle}, i.e., a cycle which visits each node in the graph exactly once, with the least weight in the graph~\citep{Hoffman1985}. This formulation naturally leads to procedures involving minimum spanning trees for tour construction or edge exchanges to improve existing tours. TSPs can also be represented as integer and linear programming problems~\citep[see, e.g.,][]{Punnen2002}. The \emph{integer programming (IP) formulation} is based on the assignment problem with additional constraint of no sub-tours: \[ \begin{array}{rl} \text{Minimize } & \sum_{i=1}^n\sum_{j=1}^n{d_{ij}x_{ij}} % = \mathrm{trace}(\mathbf{D}^T\mathbf{X}) \\[3mm] \text{Subject to } & \sum_{i=1}^n{x_{ij}=1}, \quad j=1,\ldots,n, \\ & \sum_{j=1}^n{x_{ij}=1}, \quad i=1,\ldots,n, \\ & x_{ij} = 0 \text{ or } 1 \\ & \text{no sub-tours allowed} \\ \end{array} \] The solution matrix $\mathbf{X} = (x_{ij})$ of the assignment problem represents a tour or a collection of sub-tour (several unconnected cycles) where only edges which corresponding to elements $x_{ij} = 1$ are on the tour or a sub-tour. The additional restriction that no sub-tours are allowed (called \emph{sub-tour elimination constraints}) restrict the solution to only proper tours. Unfortunately, the number of sub-tour elimination constraints grows exponentially with the number of cities which leads to an extremely hard problem. The \emph{linear programming (LP) formulation} of the TSP is given by: \[ \begin{array}{rl} \text{Minimize } & \sum_{i=1}^m{w_ix_i} = \mathbf{w}^T\mathbf{x}\\[3mm] \text{Subject to } & \mathbf{x} \in \mathcal{S} \\ \end{array} \] where $m$ is the number of edges $e_i$ in $G$, $w_i \in \mathbf{w}$ is the weight of edge $e_i$ and $\mathbf{x}$ is the incidence vector indicating the presence or absence of each edge in the tour. Again, the constraints given by $\mathbf{x} \in \mathcal{S}$ are problematic since they have to contain the set of incidence vectors of all possible Hamiltonian cycles in $G$ which amounts to a direct search of all $(n-1)!$ possibilities and thus in general is infeasible. However, relaxed versions of the linear programming problem with removed integrality and sub-tour elimination constraints are extensively used by modern TSP solvers where such a partial description of constraints is used and improved iteratively in a branch-and-bound approach. \subsection{Useful manipulations of the distance matrix} \label{sec:manipulations} Sometimes it is useful to transform the distance matrix $\mathbf{D} = (d_{ij})$ of a TSP into a different matrix $\mathbf{D'} = (d'_{ij})$ which has the same optimal solution. Such a transformation requires that for any Hamiltonian cycle $H$ in a graph represented by its distance matrix $\mathbf{D}$ the equality \begin{equation*} \sum_{i,j \in H}{d_{ij}} = \alpha \sum_{i,j \in H}{d'_{ij}} + \beta \end{equation*} holds for suitable $\alpha > 0$ and $\beta \in \mathbb{R}$. From the equality we see that additive and multiplicative constants leave the optimal solution invariant. This property is useful to rescale distances, e.g., for many solvers, distances in the interval $[0, 1]$ have to be converted into integers from~1 to a maximal value. A different manipulation is to reformulate an asymmetric TSP as a symmetric TSP. This is possible by doubling the number of cities~\citep{Jonker1983}. For each city a dummy city is added. Between each city and its corresponding dummy city a very small value (e.g., $-\infty$) is used. This makes sure that each city always occurs in the solution together with its dummy city. The original distances are used between the cities and the dummy cities, where each city is responsible for the distance going to the city and the dummy city is responsible for the distance coming from the city. The distances between all cities and the distances between all dummy cities are set to a very large value (e.g., $\infty$) which makes these edges infeasible. An example for equivalent formulations as an asymmetric TSP (to the left) and a symmetric TSP (to the right) for three cities is: \begin{equation*} \begin{pmatrix} 0 &d_{12} &d_{13} \\ d_{21} &0 &d_{23} \\ d_{31} &d_{32} &0 \\ \end{pmatrix} \Longleftrightarrow \begin{pmatrix} 0 &\infty &\infty & -\infty &d_{21} &d_{31} \\ \infty &0 &\infty & d_{12} &-\infty &d_{31} \\ \infty &\infty &0 & d_{13} &d_{23} &-\infty \\ -\infty &d_{12} &d_{13} & 0 &\infty &\infty \\ d_{21} &-\infty &d_{23} & \infty &0 &\infty \\ d_{31} &d_{32} &-\infty & \infty &\infty &0 \\ \end{pmatrix} \end{equation*} Instead of the infinity values suitably large negative and positive values can be used. The new symmetric TSP can be solved using techniques for symmetric TSPs which are currently far more advanced than techniques for ATSPs. Removing the dummy cities from the resulting tour gives the solution for the original ATSP. \subsection{Finding exact solutions for the TSP} \label{sec:exact} Finding the exact solution to a TSP with $n$ cities requires to check $(n-1)!$ possible tours. To evaluate all possible tours is infeasible for even small TSP instances. To find the optimal tour \cite{Held1962} presented the following \emph{dynamic programming} formulation: Given a subset of city indices (excluding the first city) $S \subset \{2, 3, \dots, n\}$ and $l \in S$, let $d^*(S, l)$ denote the length of the shortest path from city $1$ to city $l$, visiting all cities in $S$ in-between. For $S = \{l\}$, $d^*(S,l)$ is defined as $d_{1l}$. The shortest path for larger sets with $|S| > 1$ is \begin{equation} d^*(S,l) = \mathrm{min}_{m \in S\setminus\{l\}}\Bigl( d^*(S\setminus\{l\},m) + d_{ml}\Bigl). %\text{ for } |S| > 1. \end{equation} Finally, the minimal tour length for a complete tour which includes returning to city $1$ is \begin{equation} d^{**} = \mathrm{min}_{l \in \{2,3,\dots,n\}}\Bigl( d^*(\{2,3,\dots,n\}, l) + d_{l1}\Bigl). \end{equation} Using the last two equations, the quantities $d^*(S,l)$ can be computed recursively and the minimal tour length $d^{**}$ can be found. In a second step, the optimal permutation $\pi = \{1, i_2, i_3,\dots,i_n\}$ of city indices $1$ through $n$ can be computed in reverse order, starting with $i_n$ and working successively back to $i_2$. The procedure exploits the fact that a permutation $\pi$ can only be optimal, if \begin{equation} d^{**} = d^*(\{2,3,\dots,n\}, i_n) + d_{i_n1} \end{equation} and, for $2 \le p \le n-1$, \begin{equation} d^*(\{i_2, i_3,\dots, i_p, i_{p+1}\}, i_{p+1}) = d^*(\{i_2,i_3,\dots,i_p\}, i_p) + d_{i_pi_{p+1}}. \end{equation} The space complexity of storing the values for all $d^*(S,l)$ is $(n-1)2^{n-2}$ which severely restricts the dynamic programming algorithm to TSP problems of small sizes. However, for very small TSP instances this approach is fast and efficient. %\marginpar{time complexity if order $n^22^n$. Check!} A different method, which can deal with larger instances, uses a relaxation of the linear programming problem presented in Section~\ref{sec:formulations} and iteratively tightens the relaxation till a solution is found. This general method for solving linear programming problems with complex and large inequality systems is called \emph{cutting plane method} and was introduced by \cite{Dantzig1954}. Each iteration begins with using instead of the original linear inequality description $\mathcal{S}$ the relaxation $A\mathbf{x} \le b$, where the polyhedron $P$ defined by the relaxation contains $\mathcal{S}$ and is bounded. The optimal solution $\mathbf{x}^*$ of the relaxed problem can be obtained using standard linear programming solvers. If the $\mathbf{x}^*$ found belongs to $\mathcal{S}$, the optimal solution of the original problem is obtained, otherwise, a linear inequality can be found which is satisfied by all points in $\mathcal{S}$ but violated by $\mathbf{x}^*$. Such an inequality is called a cutting plane or cut. A family of such cutting planes can be added to the inequality system $A\mathbf{x} \le b$ to obtain a tighter relaxation for the next iteration. If no further cutting planes can be found or the improvement in the objective function due to adding cuts gets very small, the problem is branched into two sub-problems which can be minimized separately. Branching is done iteratively which leads to a binary tree of sub-problems. Each sub-problem is either solved without further branching or is found to be irrelevant because its relaxed version already produces a longer path than a solution of another sub-problem. This method is called \emph{branch-and-cut}~\citep{Padberg1990} which is a variation of the well known \emph{branch-and-bound}~\citep{Land1960} procedure. The initial polyhedron $P$ used by \cite{Dantzig1954} contains all vectors $\mathbf{x}$ for which all $x_e \in \mathbf{x}$ satisfy $0 \le x_e \le 1$ and in the resulting tour each city is linked to exactly two other cities. Various separation algorithms for finding subsequent cuts to prevent sub-tours (\emph{sub-tour elimination inequalities}) and to ensure an integer solution \citep[\emph{Gomory cuts;}][]{Gomory1963} were developed over time. The currently most efficient implementation of this method is \emph{Concorde} described in~\cite{Applegate2000}. \subsection{Heuristics for the TSP} \label{sec:heuristics} The NP-completeness of the TSP already makes it more time efficient for small-to-medium size TSP instances to rely on heuristics in case a good but not necessarily optimal solution is sufficient. TSP heuristics typically fall into two groups, tour construction heuristics which create tours from scratch and tour improvement heuristics which use simple local search heuristics to improve existing tours. In the following we will only discuss heuristics available in \pkg{TSP}, for a comprehensive overview of the multitude of TSP heuristics including an experimental comparison, we refer the reader to the book chapter by \cite{Johnson2002}. \subsubsection{Tour construction heuristics} The implemented tour construction heuristics are the nearest neighbor algorithm and the insertion algorithms. \paragraph{Nearest neighbor algorithm.} The nearest neighbor algorithm~\citep{Rosenkrantz1977} follows a very simple greedy procedure: The algorithm starts with a tour containing a randomly chosen city and then always adds to the last city in the tour the nearest not yet visited city. The algorithm stops when all cities are on the tour. An extension to this algorithm is to repeat it with each city as the starting point and then return the best tour found. This heuristic is called repetitive nearest neighbor. \paragraph{Insertion algorithms.} All insertion algorithms~\citep{Rosenkrantz1977} start with a tour consisting of an arbitrary city and then choose in each step a city $k$ not yet on the tour. This city is inserted into the existing tour between two consecutive cities $i$ and $j$, such that the insertion cost (i.e., the increase in the tour's length) $$d(i,k) + d(k,j) - d(i,j)$$ is minimized. The algorithms stop when all cities are on the tour. The insertion algorithms differ in the way the city to be inserted next is chosen. The following variations are implemented: \begin{description} \item[Nearest insertion] The city $k$ is chosen in each step as the city which is nearest to a city on the tour. \item[Farthest insertion] The city $k$ is chosen in each step as the city which is farthest from any of the cities on the tour. \item[Cheapest insertion] The city $k$ is chosen in each step such that the cost of inserting the new city is minimal. \item[Arbitrary insertion] The city $k$ is chosen randomly from all cities not yet on the tour. \end{description} The nearest and cheapest insertion algorithms correspond to the minimum spanning tree algorithm by \cite{Prim1957}. Adding a city to a partial tour corresponds to adding an edge to a partial spanning tree. For TSPs with distances obeying the triangular inequality, the equality to minimum spanning trees provides a theoretical upper bound for the two algorithms of twice the optimal tour length. The idea behind the farthest insertion algorithm is to link cities far outside into the tour first to establish an outline of the whole tour early. With this change, the algorithm cannot be directly related to generating a minimum spanning tree and thus the upper bound stated above cannot be guaranteed. However, it can was shown that the algorithm generates tours which approach $2/3$ times the optimal tour length~\citep{Johnson1985}. \subsubsection{Tour improvement heuristics} Tour improvement heuristics are simple local search heuristics which try to improve an initial tour. A comprehensive treatment of the topic can be found in the book chapter by \cite{Rego2002}. \paragraph{$k$-Opt heuristics.} The idea is to define a neighborhood structure on the set of all admissible tours. Typically, a tour $t'$ is a neighbor of another tour $t$ if $t'$ can be obtained from $t$ by deleting $k$ edges and replacing them by a set of different feasible edges (a $k$-Opt move). In such a structure, the tour can iteratively be improved by always moving from one tour to its best neighbor till no further improvement is possible. The resulting tour represents a local optimum which is called $k$-optimal. Typically, $2$-Opt~\citep{Croes1958} and $3$-Opt~\citep{Lin1965} heuristics are used in practice. \paragraph{Lin-Kernighan heuristic.} This heuristic~\citep{Lin1973} does not use a fixed value for $k$ for its $k$-Opt moves, but tries to find the best choice of $k$ for each move. The heuristic uses the fact that each $k$-Opt move can be represented as a sequence of $2$-Opt moves. It builds up a sequence of $2$-Opt moves, checking after each additional move whether a stopping rule is met. Then the part of the sequence which gives the best improvement is used. This is equivalent to a choice of one $k$-Opt move with variable $k$. Such moves are used till a local optimum is reached. By using full backtracking, the optimal solution can always be found, but the running time would be immense. Therefore, only limited backtracking is allowed in the procedure, which helps to find better local optima or even the optimal solution. Further improvements to the procedure are described by \cite{Lin1973}. \section{Computational infrastructure: the TSP package} \label{sec:infrastructure} In package~\pkg{TSP}, a traveling salesperson problem is defined by an object of class \class{TSP} (symmetric) or \class{ATSP} (asymmetric). \func{solve\_TSP} is used to find a solution, which is represented by an object of class \class{TOUR}. Figure~\ref{fig:overview} gives an overview of this infrastructure. \begin{figure} \centering \includegraphics[width=14cm]{overview} \caption{An overview of the classes in \pkg{TSP}.} \label{fig:overview} \end{figure} \class{TSP} objects can be created from a distance matrix (a \class{dist} object) or a symmetric matrix using the creator function \func{TSP} or coercion with \func{as.TSP}. Similarly, \class{ATSP} objects are created by \func{ATSP} or \func{as.ATSP} from square matrices representing the distances. In the creation process, labels are taken and stored as city names in the object or can be explicitly given as arguments to the creator functions. Several methods are defined for the classes: \begin{itemize} \item \func{print} displays basic information about the problem (number of cities and the distance measure employed). \item \func{n\_of\_cities} returns the number of cities. \item \func{labels} returns the city names. \item \func{image} produces a shaded matrix plot of the distances between cities. The order of the cities can be specified as the argument \code{order}. \end{itemize} Internally, an object of class \class{TSP} is a \class{dist} object with an additional class attribute and, therefore, if needed, can be coerced to \class{dist} or to a matrix. An \class{ATSP} object is represented as a square matrix. Obviously, asymmetric TSPs are more general than symmetric TSPs, hence, symmetric TSPs can also be represented as asymmetric TSPs. To formulate an asymmetric TSP as a symmetric TSP with double the number of cities (see Section \ref{sec:manipulations}), \func{reformulate\_ATSP\_as\_TSP} is provided. This function creates the necessary dummy cities and adapts the distance matrix accordingly. A popular format to save TSP descriptions to disk which is supported by most TSP solvers is the format used by \emph{TSPLIB}, a library of sample instances of the TSP maintained by \cite{Reinelt2004}. The \pkg{TSP} package provides \func{read\_TSPLIB} and \func{write\_TSPLIB} to read and save symmetric and asymmetric TSPs in TSPLIB format. Class \class{TOUR} represents a solution to a TSP by an integer permutation vector containing the ordered indices and labels of the cities to visit. In addition, it stores an attribute indicating the length of the tour. Again, suitable \func{print} and \func{labels} methods are provided. The raw permutation vector (i.e., the order in which cities are visited) can be obtained from a tour using \func{as.integer}. With \func{cut\_tour}, a circular tour can be split at a specified city resulting in a path represented by a vector of city indices. The length of a tour can always be calculated using \func{tour\_length} and specifying a TSP and a tour. Instead of the tour, an integer permutation vector calculated outside the \pkg{TSP} package can be used as long as it has the correct length. All TSP solvers in \pkg{TSP} can be used with the simple common interface: \begin{quote} \code{solve\_TSP(x, method, control)} \end{quote} where \code{x} is the TSP to be solved, \code{method} is a character string indicating the method used to solve the TSP and \code{control} can contain a list with additional information used by the solver. The available algorithms are shown in Table~\ref{tab:methods}. \begin{table} \caption{Available algorithms in \pkg{TSP}.} \label{tab:methods} \centering \begin{tabular}{llc} \hline \textbf{Algorithm} & \textbf{Method argument} & \textbf{Applicable to} \\ \hline Nearest neighbor algorithm & \code{"nn"} & TSP/ATSP \\ Repetitive nearest neighbor algorithm & \code{"repetitive\_nn"} & TSP/ATSP \\ Nearest insertion & \code{"nearest\_insertion"} & TSP/ATSP \\ Farthest insertion & \code{"farthest\_insertion"} & TSP/ATSP \\ Cheapest insertion & \code{"cheapest\_insertion"} & TSP/ATSP \\ Arbitrary insertion & \code{"arbitrary\_insertion"} & TSP/ATSP \\ Concorde TSP solver & \code{"concorde"} & TSP \\ 2-Opt improvement heuristic & \code{"two\_opt"} & TSP/ATSP \\ Chained Lin-Kernighan & \code{"linkern"} & TSP \\ \hline \end{tabular} \end{table} All algorithms except the Concorde TSP solver and the Chained Lin-Kernighan heuristic (a Lin-Kernighan variation described in \cite{Applegate2003}) are included in the package and distributed under the GNU Public License (GPL). For the Concorde TSP solver and the Chained Lin-Kernighan heuristic only a simple interface (using \func{write\_TSPLIB}, calling the executable and reading back the resulting tour) is included in \pkg{TSP}. The executable itself is part of the Concorde distribution, has to be installed separately and is governed by a different license which allows only for academic use. The interfaces are included since Concorde~\citep{Applegate2000,Applegate2006} is currently one of the best implementations for solving symmetric TSPs based on the branch-and-cut method discussed in section~\ref{sec:exact}. In May 2004, Concorde was used to find the optimal solution for the TSP of visiting all 24,978 cities in Sweden. The computation was carried out on a cluster with 96 Xeon 2.8 GHz nodes and took in total almost 100 CPU years. \section{Examples} \label{sec:examples} In this section we provide some examples for the use of package~\pkg{TSP}. We start with a simple example of how to use the interface of the TSP solver to compare different heuristics. Then we show how to solve related tasks, using the Hamiltonian shortest path problem as an example. Finally, we give an example of clustering using the \pkg{TSP} package. An additional application can be found in package \pkg{seriation}~\citep{TSP:Hahsler+Buchta+Hornik:2006} which uses the TSP solvers from \pkg{TSP} to order (seriate) objects given a proximity matrix. \subsection{Comparing some heuristics} In the following example, we use several heuristics to find a short path in the \code{USCA50} data set which contains the distances between the first 50 cities in the \code{USCA312} data set. The \code{USCA312} data set contains the distances between 312 cities in the USA and Canada coded as a symmetric TSP. The smaller data set is used here, since some of the heuristic solvers employed are rather slow. <<>>= library("TSP") data("USCA50") USCA50 @ We calculate tours using different heuristics and store the results in the list \code{tours}. As an example, we show the first tour which displays the method employed, the number of cities involved and the tour length. All tour lengths are compared using the dot chart in Figure~\ref{fig:dotchart}. For the chart, we add a point for the optimal solution which has a tour length of 14497. The optimal solution can be found using Concorde (\code{method = "concorde"}). It is omitted here, since Concorde has to be installed separately. <>= set.seed(1234) @ <>= methods <- c("nearest_insertion", "farthest_insertion", "cheapest_insertion", "arbitrary_insertion", "nn", "repetitive_nn", "two_opt") tours <- sapply(methods, FUN = function(m) solve_TSP(USCA50, method = m), simplify = FALSE) ## tours$concorde <- solve_TSP(tsp, method = "concorde") tours[[1]] dotchart(sort(c(sapply(tours, tour_length), optimal = 14497)), xlab = "tour length", xlim = c(0, 20000)) @ \begin{figure} \centering \includegraphics[width=11cm, trim=0 10 0 0]{TSP-dotchart_USCA50} \caption{Comparison of the tour lengths for the USCA50 data set.} \label{fig:dotchart} \end{figure} \subsection{Finding the shortest Hamiltonian path} The problem of finding the shortest Hamiltonian path through a graph (i.e., a path which visits each node in the graph exactly once) can be transformed into the TSP with cities and distances representing the graphs vertices and edge weights, respectively~\citep{Garfinkel1985}. Finding the shortest Hamiltonian path through all cities disregarding the endpoints can be achieved by inserting a `dummy city' which has a distance of zero to all other cities. The position of this city in the final tour represents the cutting point for the path. In the following we use a heuristic to find a short path in the \code{USCA312} data set. Inserting dummy cities is performed in \pkg{TSP} by \func{insert\_dummy}. <>= set.seed(1234) @ <<>>= library("TSP") data("USCA312") tsp <- insert_dummy(USCA312, label = "cut") tsp @ The TSP now contains an additional dummy city and we can try to solve this TSP. <<>>= tour <- solve_TSP(tsp, method="farthest_insertion") tour @ Since the dummy city has distance zero to all other cities, the path length is equal to the tour length reported above. The path starts with the first city in the list after the `dummy' city and ends with the city right before it. We use \func{cut\_tour} to create a path and show the first and last 6 cities on it. <<>>= path <- cut_tour(tour, "cut") head(labels(path)) tail(labels(path)) @ The tour found in the example results in a path from Lihue on Hawaii to Prince Rupert in British Columbia. Such a tour can also be visualized using the packages \pkg{sp}, \pkg{maps} and \pkg{maptools} \citep{TSP:Pebesma+Bivand:2005}. Note that he \code{if} statement and the \code{plot} in the \code{else} part in the following is not needed and only checks if the appropriate packages are installed when building this document. <>= if(require(sp) && require(maps) && require(maptools)) { library("sp") library("maps") library("maptools") data("USCA312_GPS") # create spatial coordinates and a basemap using WGS84 projection. USCA312_coords <- SpatialPointsDataFrame(cbind(USCA312_GPS$long, USCA312_GPS$lat), proj4string=CRS("+proj=longlat +datum=WGS84"), data = USCA312_GPS) USCA312_basemap <- map2SpatialLines(map("world", xlim=c(-166,-47), ylim=c(15,83), plot=FALSE), proj4string=CRS("+proj=longlat +datum=WGS84")) plot_path <- function(path){ plot(as(USCA312_coords, "Spatial"), axes = TRUE) plot(USCA312_basemap, add = TRUE, col = "gray") points(USCA312_coords, pch = 3, cex = 0.4, col = "red") path_line <- SpatialLines(list(Lines(list(Line(USCA312_coords[path,])), ID="1"))) plot(path_line, add=TRUE, col = "black") points(USCA312_coords[c(head(path,1), tail(path,1)),], pch = 19, col = "black") } plot_path(path) } else { plot(NA, xlim= c(0,1), ylim = c(0,1)); text(.5, .5, "Suggested packages not available") } @ \begin{figure} \centering \includegraphics[width=10cm, trim=0 30 0 0]{TSP-map1} \caption{A ``short'' Hamiltonian path for the USCA312 dataset.} \label{fig:map1} \end{figure} The map containing the path is presented in Figure~\ref{fig:map1}. It has to be mentioned that the path found by the used heuristic is considerable longer than the optimal path found by Concorde with a length of $34928$, illustrating the power of modern TSP algorithms. For the following two examples, we indicate how the distance matrix between cities can be modified to solve related shortest Hamiltonian path problems. These examples serve as illustrations of how modifications can be made to transform different problems into a TSP. The first problem is to find the shortest Hamiltonian path starting with a given city. In this case, all distances to the selected city are set to zero, forcing the evaluation of all possible paths starting with this city and disregarding the way back from the final city in the tour. By modifying the distances the symmetric TSP is changed into an asymmetric TSP (ATSP) since the distances between the starting city and all other cities are no longer symmetric. As an example, we choose New York as the starting city. We transform the data set into an ATSP and set the column corresponding to New York to zero before solving it. Thus, the distance to return from the last city in the path to New York does not contribute to the path length. We use the nearest neighbor heuristic to calculate an initial tour which is then improved using $2$-Opt moves and cut at New York to create a path. <>= set.seed(1234) @ <<>>= atsp <- as.ATSP(USCA312) ny <- which(labels(USCA312) == "New York, NY") atsp[, ny] <- 0 initial_tour <- solve_TSP(atsp, method="nn") initial_tour tour <- solve_TSP(atsp, method ="two_opt", control = list(tour = initial_tour)) tour path <- cut_tour(tour, ny, exclude_cut = FALSE) head(labels(path)) tail(labels(path)) @ <>= plot_path(path) @ \begin{figure} \centering \includegraphics[width=10cm, trim=0 30 0 0]{TSP-map2} \caption{A Hamiltonian path for the USCA312 dataset starting in New York.} \label{fig:map2} \end{figure} The found path is presented in Figure~\ref{fig:map2}. It begins with New York and cities in New Jersey and ends in a city in Manitoba, Canada. %The path shows the typical behavior %of the nearest neighbor heuristic with first connecting the cities close by and %then making rather big ``jumps'' for the final cities. Concorde and many advanced TSP solvers can only solve symmetric TSPs. To use these solvers, we can formulate the ATSP as a TSP using \func{reformulate\_ATSP\_as\_TSP} which introduces a dummy city for each city (see Section~\ref{sec:manipulations}). <<>>= tsp <- reformulate_ATSP_as_TSP(atsp) tsp @ After finding a tour for the TSP, the dummy cities are removed again giving the tour for the original ATSP. Note that the tour needs to be reversed if the dummy cities appear before and not after the original cities in the solution of the TSP. The following code is not executed here, since it takes several minutes to execute and Concorde has to be installed separately. Concorde finds the optimal solution with a length of $36091$. <>= tour <- solve_TSP(tsp, method = "concorde") tour <- as.TOUR(tour[tour <= n_of_cities(atsp)]) @ Finding the shortest Hamiltonian path which ends in a given city can be achieved likewise by setting the row in the distance matrix which corresponds to this city to zero. For finding the shortest Hamiltonian path we can also restrict both end points. This problem can be transformed to a TSP by replacing the two cities by a single city which contains the distances from the start point in the columns and the distances to the end point in the rows. Obviously this is again an asymmetric TSP. For the following example, we are only interested in paths starting in New York and ending in Los Angeles. Therefore, we remove the two cities from the distance matrix, create an asymmetric TSP and insert a dummy city called \code{"LA/NY"}. The distances from this dummy city are replaced by the distances from New York and the distances towards are replaced by the distances towards Los Angeles. <>= set.seed(1234) @ <<>>= m <- as.matrix(USCA312) ny <- which(labels(USCA312) == "New York, NY") la <- which(labels(USCA312) == "Los Angeles, CA") atsp <- ATSP(m[-c(ny,la), -c(ny,la)]) atsp <- insert_dummy(atsp, label = "LA/NY") la_ny <- which(labels(atsp) == "LA/NY") atsp[la_ny, ] <- c(m[-c(ny,la), ny], 0) atsp[, la_ny] <- c(m[la, -c(ny,la)], 0) @ We use the nearest insertion heuristic. <<>>= tour <- solve_TSP(atsp, method ="nearest_insertion") tour path_labels <- c("New York, NY", labels(cut_tour(tour, la_ny)), "Los Angeles, CA") path_ids <- match(path_labels, labels(USCA312)) head(path_labels) tail(path_labels) @ <>= plot_path(path_ids) @ The path jumps from New York to cities in Ontario and it passes through cities in California and Nevada before ending in Los Angeles. The path displayed in Figure~\ref{fig:map3} contains multiple crossings which indicate that the solution is suboptimal. The optimal solution generated by reformulating the problem as a TSP and using Concorde has only a tour length of $38489$. \begin{figure} \centering \includegraphics[width=10cm, trim=0 30 0 0]{TSP-map3} \caption{A Hamiltonian path for the USCA312 dataset starting in New York and ending in Los Angles.} \label{fig:map3} \end{figure} \subsection{Rearrangement clustering} Solving a TSP to obtain a clustering was suggested several times in the literature \citep[see, e.g.,][]{Lenstra1974, Alpert1997, Johnson2004}. The idea is that objects in clusters are visited in consecutive order and from one cluster to the next larger ``jumps'' are necessary. \cite{Climer2006} call this type of clustering \emph{rearrangement clustering} and suggest to automatically find the cluster boundaries of $k$ clusters by adding $k$ \emph{dummy cities} which have constant distance $c$ to all other cities and are infinitely far from each other. In the optimal solution of the TSP, the dummy cities must separate the most distant cities and thus represent optimal boundaries for $k$ clusters. For the following example, we use the well known iris data set. Since we know that the dataset contains three classes denoted by the variable \code{Species}, we insert three dummy cities into the TSP for the iris data set and perform rearrangement clustering using the default method (nearest insertion algorithm). Note that this algorithm does not find the optimal solution and it is not guaranteed that the dummy cities will present the best cluster boundaries. %\marginpar{FIXME: Was sagt Concorde dazu?} <>= set.seed(4444) @ <<>>= data("iris") tsp <- TSP(dist(iris[-5]), labels = iris[, "Species"]) tsp_dummy <- insert_dummy(tsp, n = 3, label = "boundary") tour <- solve_TSP(tsp_dummy) @ Next, we plot the TSP's permuted distance matrix using shading to represent distances. The result is displayed as Figure~\ref{fig:clustering}. Lighter areas represent larger distances. The additional red lines represent the positions of the dummy cities in the tour, which mark the cluster boundaries obtained. <>= ## plot the distance matrix image(tsp_dummy, tour, xlab = "objects", ylab ="objects") ## draw lines where the dummy cities are located abline(h = which(labels(tour)=="boundary"), col = "red") abline(v = which(labels(tour)=="boundary"), col = "red") @ \begin{figure} \centering \includegraphics[width=9cm, height=9cm, trim=0 20 0 0]{TSP-clustering} \caption{Result of rearrangement clustering using three dummy cities and the nearest insertion algorithm on the iris data set.} \label{fig:clustering} \end{figure} One pair of red horizontal and vertical lines exactly separates the darker from lighter areas. The second pair occurs inside the larger dark block. We can look at how well the partitioning obtained fits the structure in the data given by the species field in the data set. Since we used the species as the city labels in the TSP, the labels in the tour represent the partitioning with the dummy cities named `boundary' separating groups. The result can be summarized based on the run length encoding of the obtained tour labels: <<>>= out <- rle(labels(tour)) data.frame(Species = out$values, Lenghts = out$lengths, Pos = cumsum(out$lengths)) @ One boundary perfectly splits the iris data set into a group containing only examples of species `Setosa' and a second group containing examples for `Virginica' and `Versicolor'. However, the second boundary only separates several examples of species `Virginica' from other examples of the same species. Even in the optimal tour found by Concorde, this problem occurs. The reason why the rearrangement clustering fails to split the data into three groups is the closeness between the groups `Virginica' and `Versicolor'. To inspect this problem further, we can project the data points on the first two principal components of the data set and add the path segments which resulted from solving the TSP. <>= prc <- prcomp(iris[1:4]) plot(prc$x, pch = as.numeric(iris[,5]), col = as.numeric(iris[,5])) paths <- cut_tour(tour, cut = "boundary") for(p in paths) lines(prc$x[p, ]) @ \begin{figure} \centering \includegraphics[width=10cm, trim=0 20 0 0]{TSP-clustering2} \caption{The 3 path segments representing a rearrangement clustering of the iris data set. The data points are projected on the set's first two principal components. The three species are represented by different markers and colors.} \label{fig:clustering2} \end{figure} The result in shown in Figure~\ref{fig:clustering2}. The three species are identified by different markers and all points connected by a single path represent a cluster found. Clearly, the two groups to the right side of the plot are too close to be separated correctly by using just the distances between individual points. This problem is similar to the \emph{chaining effect} known from hierarchical clustering using the single-linkage method. \section{Conclusion} \label{sec:conclusion} In this paper we presented the R extension package \pkg{TSP} which implements an infrastructure to handle and solve TSPs. The package introduces classes for problem descriptions (\class{TSP} and \class{ATSP}) and for the solution (\class{TOUR}). Together with a simple interface for solving TSPs, it allows for an easy and transparent usage of the package. With the interface to Concorde, \pkg{TSP} also can use a state of the art implementation which efficiently computes exact solutions using branch-and-cut. \section*{Acknowledgments} The authors of this paper want to thank Roger Bivand for providing the code to correctly draw tours and paths on a projected map. % %\bibliographystyle{abbrvnat} \bibliography{TSP} % \end{document} TSP/inst/doc/TSP.pdf0000644000176200001440000300035513623557437013630 0ustar liggesusers%PDF-1.5 % 77 0 obj << /Length 3405 /Filter /FlateDecode >> stream xڕ˒>_ܤC|z'~;vmJ%UW/Ҏ9O0 !n̒$K_,LbԚ"O뤮Һ*ʚM\%?͖fj[.Bhפ)wpU>oo8ÿӥ3<>?d1[Λ|vj~ @Fd1apxa%UiSd7b^!nvw#Q9XL$ e ,#n _ Orbfi5"m P #C%0=A/f+Fljs[ o]4a*;5I~[, Q'$t J֩^;l=充ɲ|&"}4bk^'#Sղp 2 l,-?:)_.;UNո| <7 ]tڕߒ kt#/+uSx.'L"/rO Nfx](dPۊL b2vu?_ b7ܧWNd8:ķ舙EςU= ?0˰cM5-5w_tKْ( j/(Ap}TJ켈I`yw'$ҀATU߮wX( {Nų2Oʲ}g|מ=b*Yӱc4_h (lMj! 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USCA312_coords <- SpatialPointsDataFrame(cbind(USCA312_GPS$long, USCA312_GPS$lat), proj4string=CRS("+proj=longlat +datum=WGS84"), data = USCA312_GPS) USCA312_basemap <- map2SpatialLines(map("world", xlim=c(-166,-47), ylim=c(15,83), plot=FALSE), proj4string=CRS("+proj=longlat +datum=WGS84")) plot_path <- function(path){ plot(as(USCA312_coords, "Spatial"), axes = TRUE) plot(USCA312_basemap, add = TRUE, col = "gray") points(USCA312_coords, pch = 3, cex = 0.4, col = "red") path_line <- SpatialLines(list(Lines(list(Line(USCA312_coords[path,])), ID="1"))) plot(path_line, add=TRUE, col = "black") points(USCA312_coords[c(head(path,1), tail(path,1)),], pch = 19, col = "black") } plot_path(path) } else { plot(NA, xlim= c(0,1), ylim = c(0,1)); text(.5, .5, "Suggested packages not available") } ################################################### ### code chunk number 10: TSP.Rnw:808-809 ################################################### set.seed(1234) ################################################### ### code chunk number 11: TSP.Rnw:812-823 ################################################### atsp <- as.ATSP(USCA312) ny <- which(labels(USCA312) == "New York, NY") atsp[, ny] <- 0 initial_tour <- solve_TSP(atsp, method="nn") initial_tour tour <- solve_TSP(atsp, method ="two_opt", control = list(tour = initial_tour)) tour path <- cut_tour(tour, ny, exclude_cut = FALSE) head(labels(path)) tail(labels(path)) ################################################### ### code chunk number 12: map2 ################################################### plot_path(path) ################################################### ### code chunk number 13: TSP.Rnw:847-849 ################################################### tsp <- reformulate_ATSP_as_TSP(atsp) tsp ################################################### ### code chunk number 14: TSP.Rnw:861-863 (eval = FALSE) ################################################### ## tour <- solve_TSP(tsp, method = "concorde") ## tour <- as.TOUR(tour[tour <= n_of_cities(atsp)]) ################################################### ### code chunk number 15: TSP.Rnw:885-886 ################################################### set.seed(1234) ################################################### ### code chunk number 16: TSP.Rnw:889-899 ################################################### m <- as.matrix(USCA312) ny <- which(labels(USCA312) == "New York, NY") la <- which(labels(USCA312) == "Los Angeles, CA") atsp <- ATSP(m[-c(ny,la), -c(ny,la)]) atsp <- insert_dummy(atsp, label = "LA/NY") la_ny <- which(labels(atsp) == "LA/NY") atsp[la_ny, ] <- c(m[-c(ny,la), ny], 0) atsp[, la_ny] <- c(m[la, -c(ny,la)], 0) ################################################### ### code chunk number 17: TSP.Rnw:904-913 ################################################### tour <- solve_TSP(atsp, method ="nearest_insertion") tour path_labels <- c("New York, NY", labels(cut_tour(tour, la_ny)), "Los Angeles, CA") path_ids <- match(path_labels, labels(USCA312)) head(path_labels) tail(path_labels) ################################################### ### code chunk number 18: map3 ################################################### plot_path(path_ids) ################################################### ### code chunk number 19: TSP.Rnw:957-958 ################################################### set.seed(4444) ################################################### ### code chunk number 20: TSP.Rnw:960-964 ################################################### data("iris") tsp <- TSP(dist(iris[-5]), labels = iris[, "Species"]) tsp_dummy <- insert_dummy(tsp, n = 3, label = "boundary") tour <- solve_TSP(tsp_dummy) ################################################### ### code chunk number 21: clustering ################################################### ## plot the distance matrix image(tsp_dummy, tour, xlab = "objects", ylab ="objects") ## draw lines where the dummy cities are located abline(h = which(labels(tour)=="boundary"), col = "red") abline(v = which(labels(tour)=="boundary"), col = "red") ################################################### ### code chunk number 22: TSP.Rnw:1002-1006 ################################################### out <- rle(labels(tour)) data.frame(Species = out$values, Lenghts = out$lengths, Pos = cumsum(out$lengths)) ################################################### ### code chunk number 23: clustering2 ################################################### prc <- prcomp(iris[1:4]) plot(prc$x, pch = as.numeric(iris[,5]), col = as.numeric(iris[,5])) paths <- cut_tour(tour, cut = "boundary") for(p in paths) lines(prc$x[p, ]) TSP/inst/CITATION0000644000176200001440000000121713422436760013042 0ustar liggesusers citation(auto = meta) bibentry(bibtype = "article", title = paste("TSP -- {I}nfrastructure for the traveling", "salesperson problem"), author = { c(person("Michael", "Hahsler", email = "michael@hahsler.net"), person("Kurt", "Hornik", email = "Kurt.Hornik@R-project.org")) }, year = 2007, journal = "Journal of Statistical Software", volume = 23, number = 2, pages = "1--21", url = "http://www.jstatsoft.org/v23/i02/", month = "December", issn = "1548-7660" )