Evolutionary Algorithms: Principles and Applications
Ivan Zelinka · Wiley Encyclopedia of Electrical and Electronics Engineering · 2015
Evolutionary algorithms (EAs) are search methods that can be used for solving optimization problems. They mimic principles of natural evolution by employing a population‐based approach (or swarm‐like), associating each individual of the population with the so‐called fitness and including elements of randomness, although the random is directed through a selection process. This article presents the basic principles of evolutionary algorithms and discusses their dynamics, structure, and applications. In doing so, it is particularly shown how the fundamental understanding of natural evolution processes has cleared the ground for the origin of evolutionary algorithms. Major implementation variants and their structural as well as functional elements are discussed here with attention on examples from electrical engineering.