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A Large-Scale Multi-objective Brain Storm Optimization Algorithm Based on Direction Vectors and Variance Analysis

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Advances in Swarm Intelligence (ICSI 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13968))

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Abstract

Large-scale multi-objective optimization problems (LSMOPs) can lead to the conventional reproduction operator being inefficient for searching. Therefore, we propose a large-scale multi-objective brain storm optimization algorithm based on direction vectors and variance analysis (LMOBSO-DV) to enhance the efficiency of tackling LSMOPs. Specifically, we adopt brain storm optimization (BSO) algorithm using reference vectors to divide the population into subpopulations and guide the individuals i) in each subpopulation to search in promising directions and 2) between subpopulations to maintain diversity. We also design a new mutation operator. On a widely used LSMOPs test suites with 1000 decision variables, 2 objectives, and 3 objectives, we evaluate LMOBSO-DV’s effectiveness in comparison to other several state-of-the-art algorithms. The results of the experiment show that our proposed approach, LMOBSO-DV, outperforms the other studied algorithms.

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Acknowledgments

This work was supported in part by the Fundamental Re-search Funds for the Central Universities No. N2117005, the Joint Funds of the Natural Science Foundation of Liaoning Province und Grant 2021-KF-11-01 and the Fundamental Research Funds for the Central Universities.

Author information

Authors and Affiliations

  1. College of Software, Northeastern University, Shenyang, 110819, China

    Yang Liu, Yuee Zhou, Nan Li & Lianbo Ma

  2. Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai, China

    Lianbo Ma

  3. Neusoft Institute of Intelligent Medical Research, Shenyang, 110167, China

    Tiejun Xing

  4. School of Computer Science and Engineering Northeastern University, Shenyang, 110167, China

    Yingyou Wen

  5. Digital Factory Department, Shenyang Institute of Automation Chinese Academy of Sciences, Shenyang, 110016, China

    Chang Liu & Haibo Shi

Authors
  1. Yang Liu
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  2. Tiejun Xing
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  3. Yuee Zhou
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  4. Nan Li
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  5. Lianbo Ma
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  6. Yingyou Wen
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  7. Chang Liu
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  8. Haibo Shi
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Corresponding authors

Correspondence to Tiejun Xing or Lianbo Ma .

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Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

  3. Harbin Institute of Technology, Shenzhen, China

    Wenjian Luo

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Liu, Y. et al. (2023). A Large-Scale Multi-objective Brain Storm Optimization Algorithm Based on Direction Vectors and Variance Analysis. In: Tan, Y., Shi, Y., Luo, W. (eds) Advances in Swarm Intelligence. ICSI 2023. Lecture Notes in Computer Science, vol 13968. Springer, Cham. https://doi.org/10.1007/978-3-031-36622-2_34

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  • DOI: https://doi.org/10.1007/978-3-031-36622-2_34

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-36621-5

  • Online ISBN: 978-3-031-36622-2

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