The convergence of a multi-objective evolutionary algorithm based on grids

Authors:
Yuren Zhou;Jun He
Affiliations:
School of Computer Science and Engineering, South China University of Technology, Guangzhou, China;School of Computer Science, The University of Birmingham, Birmingham, UK
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Year:
2005

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Abstract

Evolutionary algorithms are especially suited for multi-objective optimization problems. Many evolutionary algorithms have been successfully applied to various multi-objective optimization problems. However, theoretical studies on multi-objective evolutionary algorithms are relatively scarce. This paper analyzes the convergence properties of a simple pragmatic (μ+1)-MOEA. The convergence of MOEAs is defined and the general convergence conditions are studied. Under these conditions, it is proven that the proposed (μ+1)-MOEA converges almost surely to the Pareto-optimal front.