concorde, examples which call concorde(), which solves the traveling salesman problem (TSP), mixed integer programming, and related network optimization problems.
If exact TSP solutions are desired, an optimization library is required, such as qsopt() or cplex().
The information on this web page is distributed under the MIT license.
cplex, examples which call cplex(), which is an IBM optimization package which defines and solves a variety of linear programming problems, as well as network flow problems, quadratic programming problems, and mixed integer programming problems.
lp, a dataset directory which contains datasets for linear programming, used for programs such as concorde(), cplex(), gurobi() and scip();
tsp, a dataset directory which contains test data for the traveling salesperson problem (TSP);
tsp_brute, a Python code which is given a city-to-city distance table, and solves a (small) traveling salesperson problem (TSP), using brute force.
tsp_descent, a Python code which is given a city-to-city distance table, chooses an initial tour at random, and then tries simple variations, seeking to quickly find a tour of lower cost for the traveling salesperson problem (TSP).
tsp_greedy, a Python code which is given a city-to-city distance table, and solves a small traveling salesperson problem (TSP) using the greedy algorithm. It picks a starting city at random, and then successively visits the nearest unvisited city.
tsp_moler, a Python code which seeks the shortest round trip visiting every city on a list, the traveling salesperson problem (TSP). The original MATLAB version was written by Cleve Moler.
tsp_random, a Python code which is given a city-to-city distance table, seeks a solution of the Traveling Salesperson Problem (TSP), by randomly generating round trips that visit every city, returning the tour of shortest length.
tsp_sa, an R code which is given a city-to-city distance table, and solves the traveling salesperson problem (TSP) using simulated annealing.