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ε Constrained differential evolution using halfspace partition for optimization problems

Author

Listed:
  • Wenchao Yi

    (Zhejiang University of Technology)

  • Liang Gao

    (Huazhong University of Science and Technology)

  • Zhi Pei

    (Zhejiang University of Technology)

  • Jiansha Lu

    (Zhejiang University of Technology)

  • Yong Chen

    (Zhejiang University of Technology)

Abstract

There are many efficient and effective constraint-handling mechanisms for constrained optimization problems. However, most of them evaluate all the individuals, including the worse individuals, which waste a lot of fitness evaluations. In this paper, halfspace partition mechanism based on constraint violation values is proposed. Since constraint violation information of individuals in current generation are already known, the positive side of tangent line of one point as positive halfspace is defined. A point is treated as potential point if it locates in the intersect region of two positive halfspaces. Hence, the region includes all these points has greater possibility to obtain smaller constraint violation. Only when the offspring locates in this area, the actual objective function value and constraint violation will be calculated. The estimated worse individuals will be omitted without calculating actual constraint violation and fitness function value. Four engineering optimization and a case study with the grinding optimization process are studied. The experimental results verify the effectiveness of the proposed mechanism.

Suggested Citation

  • Wenchao Yi & Liang Gao & Zhi Pei & Jiansha Lu & Yong Chen, 2021. "ε Constrained differential evolution using halfspace partition for optimization problems," Journal of Intelligent Manufacturing, Springer, vol. 32(1), pages 157-178, January.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:1:d:10.1007_s10845-020-01565-2
    DOI: 10.1007/s10845-020-01565-2
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    References listed on IDEAS

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    1. Ivona Brajević & Jelena Ignjatović, 2019. "An upgraded firefly algorithm with feasibility-based rules for constrained engineering optimization problems," Journal of Intelligent Manufacturing, Springer, vol. 30(6), pages 2545-2574, August.
    2. Ali Wagdy Mohamed, 2018. "A novel differential evolution algorithm for solving constrained engineering optimization problems," Journal of Intelligent Manufacturing, Springer, vol. 29(3), pages 659-692, March.
    3. Wenchao Yi & Yinzhi Zhou & Liang Gao & Xinyu Li & Chunjiang Zhang, 2018. "Engineering design optimization using an improved local search based epsilon differential evolution algorithm," Journal of Intelligent Manufacturing, Springer, vol. 29(7), pages 1559-1580, October.
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    Cited by:

    1. Wenchao Yi & Zhilei Lin & Youbin Lin & Shusheng Xiong & Zitao Yu & Yong Chen, 2023. "Solving Optimal Power Flow Problem via Improved Constrained Adaptive Differential Evolution," Mathematics, MDPI, vol. 11(5), pages 1-13, March.

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