An Overview of Parameter Control Methods by Self-Adaptation in Evolutionary Algorithms

Article type: Research Article

Authors: Bäck, Thomas

Affiliations: Informatik Centrum Dortmund, Joseph-von-Fraunhofer-Str. 20, D-44227 Dortmund, Germany, and Leiden University, Niels Bohrweg 1, NL-2333 CA Leiden, email: baeck@icd.de

Note: [] Address for correspondence: Informatik Centrum Dortmund, Joseph-von-Fraunhofer-Str. 20, D-44227 Dortmund, Germany

Abstract: The principle of self-adaptation in evolutionary algorithms is an important mechanism for controlling the strategy parameters of such algorithms by evolving parameter values in analogy with the usual evolution of object variables. To facilitate evolution of strategy parameters, they are incorporated into the representation of individuals and are subject to the evolutionary variation operators in a similar way as the object variables. This survey paper provides an overview of the existing techniques for the self-adaptation of strategy parameters related to mutation and recombination operators, indicating that the principle works under a variety of conditions regarding the search space of the underlying optimization problem and the method used for the variation of strategy parameters. Although a number of open questions remain, self-adaptation is identified as a generally applicable, robust and efficient method for parameter control in evolutionary algorithms.

DOI: 10.3233/FI-1998-35123404

Journal: Fundamenta Informaticae, vol. 35, no. 1-4, pp. 51-66, 1998