Co-operative Co-evolutionary Approach to Multi-objective Optimization

Authors:
Rafał Dreżewski;Krystian Obrocki
Affiliations:
Department of Computer Science, AGH University of Science and Technology, Kraków, Poland;Department of Computer Science, AGH University of Science and Technology, Kraków, Poland
Venue:
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Year:
2009

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Abstract

Co-evolutionary algorithms are evolutionary algorithms in which the given individual's fitness value estimation is made on the basis of interactions of this individual with other individuals present in the population. In this paper agent-based versions of co-operative co-evolutionary algorithms are presented and evaluated with the use of standard multi-objective test functions. The results of experiments are used to compare proposed agent-based co-evolutionary algorithms with state-of-the-art multi-objective evolutionary algorithms: SPEA2 and NSGA-II.