Multi-objective optimization technique based on co-evolutionary interactions in multi-agent system

Abstract

Co-evolutionary techniques for evolutionary algorithms help overcoming limited adaptive capabilities of evolutionary algorithms, and maintaining population diversity. In this paper the idea and formal model of agent-based realization of predator-prey co-evolutionary algorithm is presented. The effect of using such approach is not only the location of Pareto frontier but also maintaining of useful population diversity. The presented system is compared to classical multi-objective evolutionary algorithms with the use of Kursawe test problem and the problem of effective portfolio building. © Springer-Verlag Berlin Heidelberg 2007.