Robust optimization for premarshalling with uncertain priority classes

Autor(en): Boge, Sven
Goerigk, Marc
Knust, Sigrid 
Stichwörter: ALGORITHM; Business & Economics; Logistics; Management; MATHEMATICAL FORMULATION; Operations Research & Management Science; Premarshalling; Robust optimization; Storage; TREE-SEARCH PROCEDURE
Erscheinungsdatum: 2020
Herausgeber: ELSEVIER
Journal: EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Volumen: 287
Ausgabe: 1
Startseite: 191
Seitenende: 210
Zusammenfassung: 
In this paper, we consider the premarshalling problem, where items in a storage area have to be sorted for convenient retrieval. A new model for uncertainty is introduced, where the priority values induced by the retrieval sequence of the items are uncertain. We develop a robust optimization approach for this setting, study complexity issues, and provide different mixed-integer programming formulations. In a computational study using a wide range of benchmark instances from the literature, we investigate both the efficiency of the approach as well as the benefit and cost of robust solutions. We find that it is possible to achieve a considerably improved level of robustness by using just a few additional relocations in comparison to solutions which do not take uncertainty into account. (C) 2020 Elsevier B.V. All rights reserved.
ISSN: 03772217
DOI: 10.1016/j.ejor.2020.04.049

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