Brief Review of Techniques Used to Develop Adaptive Evolutionary Algorithms

Abstract

This paper presents a brief review of techniques used to allow evolutionary algorithms to adapt to optimization problems in dynamic environments, through exploration of the control parameters of genetic algorithms as well as genotypic interpreters. A description of some of the most used evolutionary techniques is included, with major emphasis on genetic algorithms and their relationship with the problem of adaptation to the environment. The article also discusses state used models to tackle these kinds of problems, including self-adaptation and genotype-phenotype mapping.