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Decomposition-based multi-objective evolutionary algorithm with mating neighborhood sizes and reproduction operators adaptation

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Abstract

Multi-objective evolutionary algorithms based on decomposition (MOEA/D) has demonstrated excellent performance in dealing with multi-objective optimization problems. As two essential issues in MOEA/D, mating neighborhood sizes and reproduction operators determine the exploitation and exploration abilities of the algorithm. This paper proposes a new decomposition-based multi-objective evolutionary algorithm with mating neighborhood sizes and reproduction operators adaptation (MOEA/D-ATO), which adaptively assigns the suitable combination of mating neighborhood size and reproduction operator to each subproblem at different searching stages. Numerical results indicate that the proposed adaptation is effective. Moreover, comparison with other adaptive steady-state MOEA/D variants and state-of-art generational MOEA/D variants shows that the proposed MOEA/D-ATO algorithm performs significantly better in terms of solution quality and CPU time.

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Acknowledgments

The work was supported in part by the National Natural Science Foundation of China (No. 61401523), in part by the Foundation for Distinguished Young Talents in Higher Education of Guangdong, China (No. 2014KQNCX002), in part by the International Science and Technology Cooperation Program of China (No. 2015DFR11050), and in part by the External Cooperation Program of Guangdong Province of China (No. 2013B051000060).

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Authors and Affiliations

  1. Department of Electronic Engineering, School of Information Science and Technology, Jinan University, Guangzhou, 510632, China

    Sheng Xin Zhang, Li Ming Zheng & Lu Liu

  2. Department of Electronics and Communication Engineering, Sun Yat-sen University, Guangzhou, 510006, China

    Shao Yong Zheng

  3. School of Electronic and Information Engineering, South China University of Technology, Guangzhou, 510640, China

    Yong Mei Pan

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  1. Sheng Xin Zhang
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  2. Li Ming Zheng
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  3. Lu Liu
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  4. Shao Yong Zheng
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Correspondence to Shao Yong Zheng.

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Communicated by V. Loia.

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Zhang, S.X., Zheng, L.M., Liu, L. et al. Decomposition-based multi-objective evolutionary algorithm with mating neighborhood sizes and reproduction operators adaptation. Soft Comput 21, 6381–6392 (2017). https://doi.org/10.1007/s00500-016-2196-9

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