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

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