Software: Genetic Algorithm for sport's pools optimization
As a volleyball player who frequently travels to play against teams in distant cities, I became curious about how sports pools are optimized to ensure fair and reasonable travel times for teams in the same category. To explore this further and delve into evolutionary algorithms, I embarked on a project to create a custom genetic algorithm using NumPy.
The custom genetic algorithm is designed to improve the current distribution of cities in sports pools. The algorithm is implemented as a Python class, making it easy to use. All you need to do is provide a list of cities that you want to allocate in the pools, and the algorithm takes care of the rest.
To showcase the algorithm’s functionality and usage, I’ve included an example in a Jupyter Notebook file, which demonstrates how to utilize the genetic algorithm with different city lists.