Genetic Algorithms

Hello. Thank you for being here. This repository belongs to the youtube videos What are Genetic Algorithms and Genetic Algorithm from Scratch in Python. If you haven't seen it, please consider watching part one of this series, to get a better understanding of this code.

Content

This repository contains the codebase I used to do the comparison between the stupid brute-force attempt to solve the Knapsack problem and the implementation of the genetic algorithms.

The codebase is structured into three modules: algorithms, problems, and utils.

Inside of algorithms you find the implementation of the brute-force approach and the non-problem-specific parts of the implementation of the genetic algorithm.

problems contains all problem-specific parts related to the Knapsack problems, like the definition of Things and the problem specific fitness function for the genetic algorithm.

utils simply contains a utility function I wrote myself to measure time using a context manager. (https://book.pythontips.com/en/latest/context_managers.html)

genetic_algo.py uses the brute-force approach to find the best solution for a given Knapsack problem and tries to find the same solution using the genetic algorithm and compares the performance.

bruteforce_time.py and genetic_time.py compare the needed time a brute-force or genetic algorithm needs for a given number of items. (Be careful the brute-force approach gets slow very fast.)

Contribution

Corrections and additions to the documentation to help fellow learners are always welcome.