tsp_brute


tsp_brute, a Python code which solves small versions of the traveling salesman problem (TSP), using brute force.

The user must prepare a file beforehand, containing the city-to-city distances. The program will request the name of this file, and then read it in. An example of such a file is:

        0  3  4  2  7
        3  0  4  6  3
        4  4  0  5  8
        2  6  5  0  6
        7  3  8  6  0
      

Licensing:

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

Languages:

tsp_brute is available in a C version and a C++ version and a Fortran90 version and a MATLAB version and an Octave version and a Python version.

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knapsack_01_brute, a Python code which uses brute force to solve small versions of the 0/1 knapsack problem;

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satisfy_brute, a Python code which uses brute force to find all assignments of values to a set of logical variables which make a complicated logical statement true.

subset_sum_brute, a Python code which uses brute force to solve the subset sum problem, to find a subset of a set of integers which has a given sum.

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 tries to optimize the traveling salesperson problem (TSP), 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.

Reference:

  1. Gerhard Reinelt,
    TSPLIB - A Traveling Salesman Problem code,
    ORSA Journal on Computing,
    Volume 3, Number 4, Fall 1991, pages 376-384.

Source Code:


Last revised on 10 November 2018.