Variable neighborhood descent heuristic for solving reverse logistics multi-item dynamic lot-sizing problems

被引：34
|
作者：
Sifaleras, Angelo [1 ]
Konstantaras, Ioannis [2 ]
机构：
[1] Univ Macedonia, Sch Informat Sci, Dept Appl Informat, 156 Egnatia Str, Thessaloniki 54636, Greece
[2] Univ Macedonia, Sch Business Adm, Dept Business Adm, 156 Egnatia Str, Thessaloniki 54636, Greece
来源：
COMPUTERS & OPERATIONS RESEARCH | 2017年 / 78卷
关键词：
Inventory; Variable Neighborhood Search; Mathematical Programming; Lot Sizing; Reverse Logistics; SUPPLY-CHAIN MANAGEMENT; PRODUCT RETURNS; SEARCH ALGORITHM; VNS APPROACH; INVENTORY; MODELS; INDUSTRY; OPTIONS; FUTURE;
D O I：
10.1016/j.cor.2015.10.004
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
The multi-product dynamic lot sizing problem with product returns and recovery is an important problem that appears in reverse logistics and is known to be NP-hard. In this paper we propose an efficient variable neighborhood descent heuristic algorithm for solving this problem. Furthermore, we present a new benchmark set with the largest instances in the literature. The computational results demonstrate that our approach outperforms the state-of-the-art Gurobi optimizer. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：385 / 392
页数：8
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