Solving the 8 queens puzzle using Genetic Algorithm. The goal of the program is to place 8 queens on a board in such a way that no queens are attacking each other.
Change global variables N and mutation_pct to experiment with different population number and mutation percentage.
- Python 3.5 or above
- Numpy 1.16 - For easy data array manipulation
- Matplotlib - For plots
cd into cloned directory. Then:
virtualenv envsource env/bin/activatepip install -r requirements.txtpython main.py
Mutation rate seemed to play a significant part in finding the solution. Whenever the algorithm converged to a single value, the mutation enabled the algorithm to still find a solution (But a solution is still not guaranteed in Genetic Algorithm).
Setting mutation percentage to a low value (1%) caused the algorithm to run to take anywhere between 1000-5000+ iterations to find a solution. Setting mutation percentage to 5% significantly attenuated this problem. The algorithm was able to obtain a solution under 1000 iterations most of the time.
This project is licensed under the MIT License - see the LICENSE.md file for details