Genetic Algorithms and the Knapsack Problem: A Beginners’ Guide
Last Updated on May 18, 2023 by Editorial Team
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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