An Extension of MOEA/D to Constrained Optimization and Adaptive Weight Adjustment

Abstract

An extended Multiobjective Evolutionary Algorithm Based on Decomposition (MOEA/D) with adaptive weight adjustment is proposed in this letter. The proposed method facilitates the search on the constraint boundary by adaptively adjusting the weights in the search process. The search performance of the proposed method is shown to be superior to that of the conventional method through numerical experiments using a constrained convex optimization problem.