Genetic Algorithms and the Knapsack Problem: A Beginners’ Guide

Author(s): Egor Howell

Originally published on Towards AI.

Get hands-on experience with genetic algorithms and learn how to solve the knapsack problem step by step

Photo by Vinicius Benedit on Unsplash

In one of my previous articles, we introduced and discussed the genetic optimization algorithm. This method is inspired by the theory of evolution where the fittest solutions in a population survive and pass on their more optimal characteristics. As a result, the weaker characteristics become extinct over time and we converge to better solutions.

For this post, I assume the reader has some basic knowledge of the inner workings of the genetic algorithm. If you are unfamiliar, I highly suggest checking out my previous post linked detailing the algorithm linked below:

Discover the power of evolutionary computing… Read the full blog for free on Medium.

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Published via Towards AI