Here is a wiki article about the problem.
In short, we are trying to place N Queen chess pieces on an N x N board so that none of them can attack each other.
If you aren't familiar with the game of chess a Queen piece can move horizontally, vertically, and diagonally.
An optimal solution uses backtracking on the placement of each queen in order to find an optimal solution.
But I will roughly follow this research article in order to solve it.
I apply evolution theory to everything in life even when it doesn't make sense. Charles Darwin would've wanted it this way.
- incorporation of async processing
time complexity of Individual.get_score()introduce backtracking algorithm for comparisonrandom "brute force" method- improve mutation to avoid local minima
- "publish" completion time for each method
- graph the performance of genetic algorithm with matplotlib
- evolution stagnates with high N value and low population
- need a way to quantify results