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Evolutionary multiobjective optimization with clustering-based self-adaptive mating restriction strategy

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Abstract

Mating restriction plays a key role in MOEAs, while clustering is an effective method to discover the similarities between individuals and therefore can assist the mating restriction. What is more, it is inappropriate to set the same mating restriction strategy for all individuals as solutions are very different between clusters. This paper proposes a multiobjective evolutionary algorithm with clustering-based self-adaptive mating restriction strategy (SRMMEA). In SRMMEA, k-means algorithm is used to cluster the population. With a certain probability, mating parents are selected from the clusters or the whole population for exploitation and exploration, respectively. To better balance the exploration and exploitation, different mating restriction probabilities are assigned to solutions in different clusters. Moreover, the mating restriction probability is updated at each generation according to the number of newly generated individuals in each cluster. SRMMEA is compared with some state-of-the-art multiobjective evolutionary methods on a number of test instances. Experimental results demonstrate SRMMEA’s superiority over other comparison algorithms.

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Acknowledgements

This study was funded by China Aerospace Science and Technology Innovation Foundation (Grant number: CAST.No.JZ20160008) and National Natural Science Foundation of China (Grant number: 61333003).

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Authors and Affiliations

  1. Center for Control Theory and Guidance Technology, Harbin Institute of Technology, Harbin, 150001, China

    Xin Li & Shenmin Song

  2. Beijing Electro-mechanical Engineering Institute, Beijing, 100074, China

    Hu Zhang

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  1. Xin Li
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  2. Shenmin Song
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  3. Hu Zhang
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Correspondence to Shenmin Song.

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This article does not contain any studies with human participants performed by any of the authors.

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Communicated by V. Loia.

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Li, X., Song, S. & Zhang, H. Evolutionary multiobjective optimization with clustering-based self-adaptive mating restriction strategy. Soft Comput 23, 3303–3325 (2019). https://doi.org/10.1007/s00500-017-2990-z

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