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A novel hybrid immune clonal selection algorithm for the constrained corridor allocation problem

Author

Listed:
  • Junqi Liu

    (Southwest Jiaotong University
    Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province)

  • Zeqiang Zhang

    (Southwest Jiaotong University
    Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province)

  • Feng Chen

    (Southwest Jiaotong University
    Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province)

  • Silu Liu

    (Southwest Jiaotong University
    Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province)

  • Lixia Zhu

    (Southwest Jiaotong University
    Technology and Equipment of Rail Transit Operation and Maintenance Key Laboratory of Sichuan Province)

Abstract

Aiming at the lack of relevant research on relationship constraints between facilities in the corridor allocation problem (CAP). In this paper, fixed position constraints and ordering constraints are considered in CAP, and the logistics cost is minimized. Considering that the existing search technology is complicated and time-consuming in dealing with such constrained CAP (cCAP), and immune clone selection algorithm with variable neighborhood operation (ICSAVNS) is provided for solving this problem. Two approaches to initial solution generation are designed to improve the quality of the initial population. A variable neighborhood search operator is embedded to improve the accuracy of the local search. A threshold is set in the mutation operation of the ICSAVNS to achieve population expansion better. A double index of sequences consisting of affinity values and constrained facility index values is used to select and reselect, achieving population compression in the clonal selection part. Finally, by exactly solving the model, the rationality of the model is verified. The hybrid clone selection algorithm is used to solve the cCAP and cbCAP benchmark instances of different sizes, and compared with the state-of-the-art optimization algorithms. The results show that the proposed algorithm exhibits better performance.

Suggested Citation

  • Junqi Liu & Zeqiang Zhang & Feng Chen & Silu Liu & Lixia Zhu, 2022. "A novel hybrid immune clonal selection algorithm for the constrained corridor allocation problem," Journal of Intelligent Manufacturing, Springer, vol. 33(4), pages 953-972, April.
    • Handle: RePEc:spr:joinma:v:33:y:2022:i:4:d:10.1007_s10845-020-01693-9
    DOI: 10.1007/s10845-020-01693-9
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    References listed on IDEAS

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    1. Qiaoyu Zhang & Yan Lin, 2024. "Integrating multi-agent reinforcement learning and 3D A* search for facility layout problem considering connector-assembly," Journal of Intelligent Manufacturing, Springer, vol. 35(7), pages 3393-3418, October.

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