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Title: Variable neighborhood descent heuristic for solving reverse logistics multi-item dynamic lot-sizing problems
Authors: Sifaleras, Angelo
Konstantaras, Ioannis
Subjects: FRASCATI::Natural sciences::Mathematics::Applied Mathematics
FRASCATI::Natural sciences::Computer and information sciences
Keywords: Inventory
Variable Neighborhood Search
Mathematical Programming
Lot Sizing
Reverse Logistics
Issue Date: 2017
Publisher: Elsevier
Source: Computers & Operations Research
Volume: 78
First Page: 385
Last Page: 392
Abstract: 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.
ISSN: 03050548
Other Identifiers: 10.1016/j.cor.2015.10.004
Appears in Collections:Department of Applied Informatics

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