tsp_anneal


tsp_anneal, a MATLAB code which solves the traveling salesperson problem (TSP) using simulated annealing.

Licensing:

The information on this web page is distributed under the MIT license.

Languages:

tsp_anneal is available in a Fortran90 version and a MATLAB version and an Octave version and a Python version and an R version.

Related Data and Programs:

tsp_anneal_test

tsp, a dataset directory which contains test data for the traveling salesperson problem (TSP) including the AT&T 48 state capital test, and Dantzig's 42 city test;

tsp_att48, a MATLAB code which returns the (x,y) coordinates of the cities that constitute the AT&T 48 state challenge for the Traveling Salesman Problem (TSP).

tsp_brute, a MATLAB code which is given a table of city locations, and solves a (small) traveling salesperson problem (TSP), using brute force.

tsp_dantzig42, a MATLAB code which returns the (x,y) coordinates of the cities that constitute the Dantzig 42 state challenge for the Traveling Salesman Problem (TSP). The minimal tour is known to have length 699.

tsp_display, a MATLAB code which displays the solution of a Traveling Salesman Problem (TSP).

tsp_moler, a MATLAB code which tries to optimize the traveling salesperson problem (TSP), written by Cleve Moler.

tsp_nearest, a MATLAB code which is given a table of city locations, and solves a small traveling salesperson problem (TSP) using the nearest neighbor algorithm. It picks a starting city at random, and then successively visits the nearest unvisited city.

tsp_random, a MATLAB code which is given a table of city locations, seeks a solution of the Traveling Salesperson Problem (TSP), by randomly generating round trips that visit every city, returning the tour of shortest length.

Author:

Original R code by James Howard; This version by John Burkardt.

Reference:

  1. William Cook,
    In Pursuit of the Traveling Salesman,
    Princeton University Press, 2012,
    ISBN13 978-0-691-16352-9.
  2. James Howard,
    Computational Methods for Numerical Analysis with R,
    CRC Press, 2017,
    ISBN13: 978-1-4987-2363-3.
  3. https://CRAN.R-project.org/package=cmna

Source Code:


Last revised on 04 June 2026.