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A reduced variable neighborhood search algorithm for uncapacitated multilevel lot-sizing problems

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

Abstract

Multilevel lot-sizing (MLLS) problems, which involve complicated product structures with interdependence among the items, play an important role in the material requirement planning (MRP) system of modern manufacturing/assembling lines. In this paper, we present a reduced variable neighborhood search (RVNS) algorithm and several implemental techniques for solving uncapacitated MLLS problems. Computational experiments are carried out on three classes of benchmark instances under different scales (small, medium, and large). Compared with the existing literature, RVNS shows good performance and robustness on a total of 176 tested instances. For the 96 small-sized instances, the RVNS algorithm can find 100% of the optimal solutions in less computational time; for the 40 medium-sized and the 40 large-sized instances, the RVNS algorithm is competitive against other methods, enjoying good effectiveness as well as high computational efficiency. In the calculations, RVNS updated 7 (17.5%) best known solutions for the medium-sized instances and 16 (40%) best known solutions for the large-sized instances.

Suggested Citation

  • Xiao, Yiyong & Kaku, Ikou & Zhao, Qiuhong & Zhang, Renqian, 2011. "A reduced variable neighborhood search algorithm for uncapacitated multilevel lot-sizing problems," European Journal of Operational Research, Elsevier, vol. 214(2), pages 223-231, October.
    • Handle: RePEc:eee:ejores:v:214:y:2011:i:2:p:223-231
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    Cited by:

    1. Patrícia Lopes Costa & Ana Margarida Graça & Pedro Marques-Quinteiro & Catarina Marques Santos & António Caetano & Ana Margarida Passos, 2013. "Multilevel Research in the Field of Organizational Behavior," SAGE Open, , vol. 3(3), pages 21582440134, August.
    2. 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.
    3. 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.
    4. Devika, K. & Jafarian, A. & Nourbakhsh, V., 2014. "Designing a sustainable closed-loop supply chain network based on triple bottom line approach: A comparison of metaheuristics hybridization techniques," European Journal of Operational Research, Elsevier, vol. 235(3), pages 594-615.

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