tsp_brute, a Python code which is given a table of city locations, and solves small versions of the traveling salesman problem (TSP), using brute force.
The information on this web page is distributed under the MIT license.
tsp_brute is available in a C version and a C++ version and a Fortran77 version and a Fortran90 version and a MATLAB version and an Octave version and a Python version.
closest_pair_brute, a Python code which uses brute force to solve a 2D version of the closest pair problem, which identifies the closest pair of points in a given collection.
concorde, examples which call concorde(), which solves the traveling salesman problem (TSP), mixed integer programming, and related network optimization problems.
knapsack_01_brute, a Python code which uses brute force to solve small versions of the 0/1 knapsack problem;
matrix_chain_brute, a Python code which finds the cost of the most efficient ordering to use when multiplying a sequence of matrices, using brute force.
partition_brute, a Python code which uses a brute force method to find solutions of the partition problem, in which a set of integers must be split into two subsets with equal sum.
python_combinatorics, a Python code which considers a variety of problems in combinatorics involving counting, combinations, permutations, and so on.
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, 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_anneal, a Python code which is given a table of city locations, and solves the traveling salesperson problem (TSP) using simulated annealing.
tsp_att48, a Python 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_display, a Python code which displays the solution of a Traveling Salesman Problem (TSP).
tsp_moler, a Python code which tries to optimize the traveling salesperson problem (TSP), written by Cleve Moler.
tsp_nearest, a Python 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 Python 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.
att06, att09, att12, att24 are the first 6, 9, 12, and 24 cities in the AT&T 48 city dataset. They are provided as warmup for the full 48 challenge. The brute force approach was only tried on the smaller cases!
