Evolving from genetic algorithms to flexible evolution agents

Abstract

In this paper an alternative design for the internal structure of Evolutionary Algorithms is presented and a first implementation of such structure is tested. In order to improve the internal structure architecture of Evolutionary Algorithms as well as to learn which the adequate values of parameters and/or structure of operators are, a review showing the successive efforts made in this line is included. In this way, the evolution from the simplest GA to the present advanced structures is illustrated using figures which summarize their characteristics. Based on the analysis of such figures, a new and more flexible internal structure design is introduced maintaining the benefits of its predecessors but permitting a major degree of self-adaptation, because now the parameters, the operators and the structure can adapt themselves at each optimization step. This new structure is named a Flexible Evolution Agent (FEA). Results of a first software implementation are presented and compared using several well-known test functions.