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Heuristics for the multi-item capacitated lot-sizing problem with lost sales

Abstract : This paper deals with the Multi-item Capacitated Lot-Sizing problem with setup times and lost sales. Because of lost sales, demands can be partially or totally lost. To find a good lower bound, we use a Lagrangian relaxation of the capacity constraints, when single-item uncapacitated lot-sizing problems with lost sales have to be solved. Each subproblem is solved using an adaptation of the O(T^2) dynamic programming algorithm of Aksen et al. [5]. To find feasible solutions, we propose a non-myopic heuristic based on a probing strategy and a refining procedure. We also propose a metaheuristic based on the adaptive large neighborhood search principle to improve solutions. Some computational experiments showing the effectiveness and limitation of each approach are presented.
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Contributor : Stéphane Dauzère-Pérès Connect in order to contact the contributor
Submitted on : Thursday, September 20, 2012 - 8:56:27 AM
Last modification on : Monday, November 16, 2020 - 11:58:02 AM



Nabil Absi, Boris Detienne, Stéphane Dauzère-Pérès. Heuristics for the multi-item capacitated lot-sizing problem with lost sales. Computers and Operations Research, Elsevier, 2013, 40 (1), pp.264-272. ⟨10.1016/j.cor.2012.06.010⟩. ⟨emse-00733895⟩



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