How Genetic Algorithms Work
Genetic algorithms (GAs) are inspired by biology where only the fittest genes survive. It is based on Charles Darwin’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 crossover and mutation 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’s way of optimizing over genetic diversity and we can co-opt this approach for tackling other optimization problems. ...