R package TSP - Infrastructure for the Traveling Salesperson Problem
Introduction
The TSP package (Hahsler and Hornik 2007) provides the basic infrastructure and some algorithms for the traveling salesman problems (symmetric, asymmetric and Euclidean TSPs). The package provides some fast implementations of simple algorithms including:
- Tour construction heuristics
- Insertion algorithms: nearest insertion, farthest insertion, cheapest insertion, arbitrary insertion (Rosenkrantz, Stearns, and Philip M. Lewis 1977)
- Nearest neighbor methods: Nearest neighbor and repetitive nearest neighbor (Rosenkrantz, Stearns, and Philip M. Lewis 1977)
- Tour improvement methods
- Two-opt heuristic (Croes 1958)
- Simulated annealing (Kirkpatrick, Gelatt, and Vecchi 1983)
- State-of-the-art solver interfaces
- Concorde TSP solver interface (Applegate et al. 2000, 2006)
- Concorde Chained-Lin-Kernighan heuristic interface (Applegate, Cook, and Rohe 2003)
The package can read and write the TSPLIB format (Reinelt 1991) and it can solve many of the problems in the TSPLIB95 problem library (local copy of the archive).
The following R packages use TSP:
archetypes,
cholera,
condvis,
CRTspat,
ForagingOrg,
ggEDA,
isocir,
jocre,
MLCOPULA,
nilde,
nlnet,
PairViz,
SCORPIUS,
sensitivity,
seriation,
sfnetworks,
tspmeta,
VineCopula
To cite package ‘TSP’ in publications use:
Hahsler M, Hornik K (2007). “TSP - Infrastructure for the traveling salesperson problem.” Journal of Statistical Software, 23(2), 1-21. ISSN 1548-7660, <doi:10.18637/jss.v023.i02> https://doi.org/10.18637/jss.v023.i02.
@Article{,
title = {TSP -- {I}nfrastructure for the traveling salesperson problem},
author = {Michael Hahsler and Kurt Hornik},
year = {2007},
journal = {Journal of Statistical Software},
volume = {23},
number = {2},
pages = {1--21},
doi = {10.18637/jss.v023.i02},
month = {December},
issn = {1548-7660},
}
Installation
Stable CRAN version: Install from within R with
install.packages("TSP")
Current development version: Install from r-universe.
install.packages("TSP",
repos = c("https://mhahsler.r-universe.dev",
"https://cloud.r-project.org/"))
Usage
Load a data set with 312 cities (USA and Canada) and create a TSP object.
library("TSP")
data("USCA312")
tsp <- TSP(USCA312)
tsp
## object of class 'TSP'
## 312 cities (distance 'euclidean')
Find a tour using the default heuristic.
tour <- solve_TSP(tsp)
tour
## object of class 'TOUR'
## result of method 'arbitrary_insertion+two_opt' for 312 cities
## tour length: 41202
Show the first few cities in the tour.
head(tour, n = 10)
## Columbus, GA Atlanta, GA Macon, GA
## 65 12 157
## Tallahassee, FL Gainesville, FL Tampa, FL
## 274 101 275
## Saint Petersburg, FL Sarasota, FL Key West, FL
## 234 247 136
## San Juan, PR
## 243
Visualize the complete tour.
library(maps)
data("USCA312_GPS")
plot((USCA312_GPS[, c("long", "lat")]), cex = 0.3)
map("world", col = "gray", add = TRUE)
polygon(USCA312_GPS[, c("long", "lat")][tour, ], border = "red")
An online example application of TSP can be found on shinyapps.
Help and Bug Reports
You can find Q&A’s and ask your own questions at https://stackoverflow.com/search?q=TSP+R
Please submit bug reports to https://github.com/mhahsler/TSP/issues