Please use this identifier to cite or link to this item:
https://ruomo.lib.uom.gr/handle/7000/605
Title: | A Survey on Variable Neighborhood Search Methods for Supply Network Inventory |
Authors: | Sifaleras, Angelo Konstantaras, Ioannis |
Editors: | Bychkov, Ilya Kalyagin, Valery A. Pardalos, Panos M. Prokopyev, Oleg |
Type: | Conference Paper |
Subjects: | FRASCATI::Natural sciences::Mathematics::Applied Mathematics FRASCATI::Social sciences::Economics and Business::Business and Management FRASCATI::Natural sciences::Computer and information sciences |
Keywords: | Supply chain networks Inventory optimization Variable neighborhood search |
Issue Date: | 23-Feb-2020 |
Publisher: | Springer |
Volume: | 315 |
First Page: | 71 |
Last Page: | 82 |
Volume Title: | Network Algorithms, Data Mining, and Applications |
Part of Series: | Springer Proceedings in Mathematics & Statistics |
Part of Series: | Springer Proceedings in Mathematics & Statistics |
Abstract: | Over the past two decades, reverse logistics and closed-loop supply chain networks have gained substantial interest in business and academia. The dynamic lot-sizing problem with product returns and recovery is one of the most extensively researched topics in inventory control literature. Several interesting generalizations of this optimization problem have lately emerged that include the multiproduct case, the case with capacity constraints, and others. In this chapter, we present recent successful applications of variable neighborhood search (VNS) for the efficient solution of such problems, review the state-of-the-art solution methods, and also discuss some future research directions. |
URI: | https://doi.org/10.1007/978-3-030-37157-9_5 https://ruomo.lib.uom.gr/handle/7000/605 |
ISBN: | 978-3-030-37156-2 978-3-030-37157-9 |
ISSN: | 2194-1009 2194-1017 |
Other Identifiers: | 10.1007/978-3-030-37157-9_5 |
Appears in Collections: | Department of Applied Informatics |
Files in This Item:
File | Description | Size | Format | |
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A_survey_on_variable_neighborhood_search_methods_for_supply_network_inventory.pdf | 149,58 kB | Adobe PDF | View/Open |
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