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.
Complete list of metadatas

https://hal-emse.ccsd.cnrs.fr/emse-00733895
Contributor : Stéphane Dauzère-Pérès <>
Submitted on : Thursday, September 20, 2012 - 8:56:27 AM
Last modification on : Saturday, March 23, 2019 - 1:22:42 AM

Identifiers

Citation

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⟩

Share

Metrics

Record views

224