Agent-based co-operative co-evolutionary algorithm for multi-objective optimization

Co-evolutionary algorithms are a special type of evolutionary algorithms, in which the fitness of each individual depends on other individuals' fitness. Such algorithms are applicable in the case of problems for which the formulation of explicit fitness function is difficult or impossible. Co-evolutionary algorithms also maintain population diversity better than "classical" evolutionary algorithms. In this paper the agent-based version of co-operative co-evolutionary algorithm is presented and applied to multi-objective test problems. The proposed technique is also compared to two "classical" multi-objective evolutionary algorithms.