Traveling Salesman Genetic

This Project Solves the Traveling Sales Person Problem using genetic algorithm with the following properties:

• Chromosomes decoded as cycles (solutions) of traveling
• Order 1 crossover
• Swap mutation
• Complete generation replacement
• Roulette Wheel Technique for choosing parents
• Negative of cycle distance as fitness

Documentation

The code is documented using Google Style Docstring but for a detailed documentation read the documentation.md

Requirements

• Python Version 3+
• numpy
• matplotlib

Running:

Run the project by running TSPG.py

Here is the results for input1.txt :

and input2.txt :

Both runs use the following parameters:

• n = 20
• k = 100
• max_generation = 1000
• crossover_probability = 0.99
• mutation_probability = 0.01

License

The MIT License. Copyright (c) 2017 Amin Fadaee

About Author

Amin Fadaee