Robust formulations for economic lot-sizing problem with remanufacturing

被引:18
作者
Attila, Oeykue Naz [1 ]
Agra, Agostinho [2 ,3 ]
Akartunah, Kerem [1 ]
Arulselvan, Ashwin [1 ]
机构
[1] Univ Strathclyde, Dept Management Sci, Glasgow, Lanark, Scotland
[2] Univ Aveiro, Dept Math, Aveiro, Portugal
[3] Univ Aveiro, CIDMA, Aveiro, Portugal
关键词
Integer programming; Lot-sizing; Robust optimization; Extended reformulations; Decomposition; REVERSE LOGISTICS; OPTIMIZATION;
D O I
10.1016/j.ejor.2020.06.016
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
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. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:496 / 510
页数:15
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