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Optimizing a stochastic disassembly line balancing problem with task failure via a hybrid variable neighborhood descent-artificial bee colony algorithm

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Listed:
  • Hongfei Guo
  • Linsheng Zhang
  • Yaping Ren
  • Yun Li
  • Zhongwei Zhou
  • Jianzhao Wu

Abstract

A disassembly line is an effective disassembly system to recover end-of-life products. In real life, as end-of-life products are subject to varying degrees of wear and tear, task failure may occur in the disassembly process. In this paper, the task failure risks are considered, and an expected profit-based stochastic disassembly line balancing problem is studied. First, a mathematical model is presented to maximise the expected recovering profit with task failures. Then, a hybrid metaheuristic approach is developed to efficiently solve the proposed model, which is integrated with a variable neighbourhood descent method and an artificial bee colony algorithm. Finally, the effectiveness and robustness of the proposed algorithm are verified by three cases, and experiment results show that the solution performance of the proposed approach is superior to the other three existing methods.

Suggested Citation

  • Hongfei Guo & Linsheng Zhang & Yaping Ren & Yun Li & Zhongwei Zhou & Jianzhao Wu, 2023. "Optimizing a stochastic disassembly line balancing problem with task failure via a hybrid variable neighborhood descent-artificial bee colony algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 61(7), pages 2307-2321, April.
    • Handle: RePEc:taf:tprsxx:v:61:y:2023:i:7:p:2307-2321
    DOI: 10.1080/00207543.2022.2069524
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    Cited by:

    1. He, Junkai & Chu, Feng & Dolgui, Alexandre & Anjos, Miguel F., 2024. "Multi-objective disassembly line balancing and related supply chain management problems under uncertainty: Review and future trends," International Journal of Production Economics, Elsevier, vol. 272(C).

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