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Title: Robust formulations for economic lot-sizing problem with remanufacturing
Author: Attila, Öykü Naz
Agra, Agostinho
Akartunalı, Kerem
Arulselvan, Ashwin
Keywords: Integer programming
Robust optimization
Extended reformulations
Issue Date: 16-Jan-2021
Publisher: Elsevier
Abstract: In this paper, we consider a lot-sizing problem with the remanufacturing option under parameter uncertainties imposed on demands and returns. Remanufacturing has recently been a fast growing area of interest for many researchers due to increasing awareness on reducing waste in production environments, and in particular studies involving remanufacturing and parameter uncertainties simultaneously are very scarce in the literature. We first present a min-max decomposition approach for this problem, where decision maker’s problem and adversarial problem are treated iteratively. Then, we propose two novel extended reformulations for the decision maker’s problem, addressing some of the computational challenges. An original aspect of the reformulations is that they are applied only to the latest scenario added to the decision maker’s problem. Then, we present an extensive computational analysis, which provides a detailed comparison of the three formulations and evaluates the impact of key problem parameters. We conclude that the proposed extended reformulations outperform the standard formulation for a majority of the instances. We also provide insights on the impact of the problem parameters on the computational performance.
Peer review: yes
DOI: 10.1016/j.ejor.2020.06.016
ISSN: 0377-2217
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Appears in Collections:CIDMA - Artigos
DMat - Artigos
OGTCG - Artigos

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