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A set of algorithms for solving optimization problems, such as the traveling salesman problem.

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Traveller Salesman Problem

This project is a collection of optimization algorithms to solve the traveling salesman problem. However, it is also possible to adapt it for other problems such as the backpacking problem.

Screenshot

Thus, the following algorithms are implemented:

  • local search (ls)
  • simulated annealing (sa)
  • variable neighborhood search (vns)
  • tabu search (ts)
  • genetic algorithm (ga)
  • ant colony optimization (aco)

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development purposes.

Prerequisites

Make sure that g++ or mingw-w64 is installed.

Installing

First you have to clone the git project:

git clone https://github.com/msommacal/tsp.git

Then you can compile the project using Make:

make

You can compile for Windows with the following target:

make win

Usage

To execute the software, you only need to use the following command:

bin/tsp data/data.txt

You can also execute only some algorithms with special commands:

bin/tsp --bf --vns --ts data/data.txt

Benchmark

Benchmark

License

This project is licensed under the GNU General Public License - see the LICENSE.md file for details.

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A set of algorithms for solving optimization problems, such as the traveling salesman problem.

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