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A variable neighborhood search with an effective local search for uncapacitated multilevel lot-sizing problems

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  • Xiao, Yiyong
  • Zhang, Renqian
  • Zhao, Qiuhong
  • Kaku, Ikou
  • Xu, Yuchun

Abstract

In this study, we improved the variable neighborhood search (VNS) algorithm for solving uncapacitated multilevel lot-sizing (MLLS) problems. The improvement is twofold. First, we developed an effective local search method known as the Ancestors Depth-first Traversal Search (ADTS), which can be embedded in the VNS to significantly improve the solution quality. Second, we proposed a common and efficient approach for the rapid calculation of the cost change for the VNS and other generate-and-test algorithms. The new VNS algorithm was tested against 176 benchmark problems of different scales (small, medium, and large). The experimental results show that the new VNS algorithm outperforms all of the existing algorithms in the literature for solving uncapacitated MLLS problems because it was able to find all optimal solutions (100%) for 96 small-sized problems and new best-known solutions for 5 of 40 medium-sized problems and for 30 of 40 large-sized problems.

Suggested Citation

  • Xiao, Yiyong & Zhang, Renqian & Zhao, Qiuhong & Kaku, Ikou & Xu, Yuchun, 2014. "A variable neighborhood search with an effective local search for uncapacitated multilevel lot-sizing problems," European Journal of Operational Research, Elsevier, vol. 235(1), pages 102-114.
    • Handle: RePEc:eee:ejores:v:235:y:2014:i:1:p:102-114
    DOI: 10.1016/j.ejor.2013.10.025
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    Cited by:

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    2. Zeng, Zhizhong & Yu, Xinguo & He, Kun & Huang, Wenqi & Fu, Zhanghua, 2016. "Iterated Tabu Search and Variable Neighborhood Descent for packing unequal circles into a circular container," European Journal of Operational Research, Elsevier, vol. 250(2), pages 615-627.
    3. Yiyong Xiao & Meng You & Xiaorong Zuo & Shenghan Zhou & Xing Pan, 2018. "The Uncapacitatied Dynamic Single-Level Lot-Sizing Problem under a Time-Varying Environment and an Exact Solution Approach," Sustainability, MDPI, vol. 10(11), pages 1-14, October.
    4. Sifaleras, Angelo & Konstantaras, Ioannis & Mladenović, Nenad, 2015. "Variable neighborhood search for the economic lot sizing problem with product returns and recovery," International Journal of Production Economics, Elsevier, vol. 160(C), pages 133-143.
    5. Tao Wu, 2022. "Predictive Search for Capacitated Multi-Item Lot Sizing Problems," INFORMS Journal on Computing, INFORMS, vol. 34(1), pages 385-406, January.
    6. Yiyong Xiao & Abdullah Konak, 2017. "A variable neighborhood search for the network design problem with relays," Journal of Heuristics, Springer, vol. 23(2), pages 137-164, June.
    7. Xiao, Yiyong & Konak, Abdullah, 2016. "The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 146-166.
    8. Zhou, Shenghan & Zhou, Yuliang & Zuo, Xiaorong & Xiao, Yiyong & Cheng, Yang, 2018. "Modeling and solving the constrained multi-items lot-sizing problem with time-varying setup cost," Chaos, Solitons & Fractals, Elsevier, vol. 116(C), pages 202-207.
    9. Gansterer, Margaretha & Födermayr, Patrick & Hartl, Richard F., 2021. "The capacitated multi-level lot-sizing problem with distributed agents," International Journal of Production Economics, Elsevier, vol. 235(C).

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