Using Two Reproduction Operators for Balancing Convergence and Diversity in MOEA/D

Reproduction operator is an important component used in multi-objective evolutionary based on decomposition (MOEA/D). This paper proposes two reproduction operators with different characteristics and studies how to employ these two operators to balance the convergence and the diversity in MOEA/D. One of the reproduction operators is a Levy flights crossover and improved polynomial mutation, and the other one is orthogonal crossover operator. We come up with a scheme to incorporate these two reproduction operators in MOEA/D and propose a new algorithm, i.e., MOEA/D–FL&OX, and compares the proposed algorithm with MOEA/D-DE on the test instances. The experimental results show that MOEA/D-FL&OX could significantly outperform the compared algorithms. It suggests that the proposed algorithm is an effective and competitive candidate for multi-objective optimization.

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