A Brief Introduction to Evolutionary Algorithms
Évelyne Lutton, Nathalie Perrot, Alberto Paolo Tonda · 2016
Evolutionary algorithms (EAs), also known as genetic algorithms (GAs), evolution strategies (ESs), evolutionary programming (EP) or artificial evolution, are stochastic optimization methods based on a simplified model of natural evolution, according to Darwin's theory. This chapter presents an overview of these methods, with a focus on their extreme versatility, which is one of the reasons for their success in a large variety of application domains. It has to be noted that artificial evolution is not limited to pure optimization applications, as there are other uses of these techniques, in particular when they are embedded in an interactive framework. Implementations of EAs are, however, computationally expensive, and a fine apperception of artificial evolution mechanisms helps to efficiently tune their various components. The most efficient applications of EAs are often based on hybridizations with other optimization techniques.