https://datathrillz.com/tags/genetic-algorithm/Recent content in Genetic Algorithm on DataThrillzHugoen-usMon, 10 Aug 2020 16:44:04 +0000https://datathrillz.com/posts/2020-08-10-genetic-algorithm/Mon, 10 Aug 2020 16:44:04 +0000https://datathrillz.com/posts/2020-08-10-genetic-algorithm/<p>Genetic algorithms (GAs) are inspired by biology where only the fittest genes survive. It is based on Charles Darwin&rsquo;s Natural Selection theory. We start with 2 parent chromosomes that each contain an ordered set of genes. Each parent contributes some of their genes when they mate to create children chromosomes. There is a randomness to the mating process so that each child has a diverse set of genes. This diversity is created by the <strong>crossover</strong> and <strong>mutation</strong> processes. Over time and with sufficient genetic diversity, the fittest genes, representing optimal characteristics for the species to survive, be come dominant and are propagated. This is nature&rsquo;s way of optimizing over genetic diversity and we can co-opt this approach for tackling other optimization problems.</p>