On the Effect of Product Demand Correlation on the Storage Space Allocation Problem in a Fast-Pick Area of a Warehouse

Felipe I.Gré Carafí, Alberto Ossa Ortiz de Zevallos, Rosa G. González-Ramírez*, Mario C. Velez-Gallego

*Autor correspondiente de este trabajo

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

The storage location assignment problem (SLAP), also known as the slotting problem involves the decisions of how much and where should be stored each stock keeping unit (SKU) in the fast-pick area with the aim to minimize total order-picking and replenishment costs associated to the distance traveled by the picking operators. Motivated by this, we propose to analyze the impact of SKUs demand correlation on the slotting decisions. Based on an experimental design, the effects of SKUs with correlated demand are analyzed. Results show that the most significant factor with respect to the total distance traveled is the number of orders, followed by the capacity of the bins and the number of bins in each location. Results of an instance solved to optimality by a commercial solver and a greedy heuristic in which the latter does not consider the demand correlation illustrate the impact that demand correlation has on the solution obtained. © 2021, Springer Nature Switzerland AG.
Idioma originalInglés
Título de la publicación alojadaComputational Logistics - 12th International Conference, ICCL 2021, Proceedings
EditoresMartijn Mes, Eduardo Lalla-Ruiz, Stefan Voß
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas282-295
Número de páginas14
ISBN (versión impresa)9783030876715
DOI
EstadoPublicada - 2021
Evento12th International Conference on Computational Logistics, ICCL 2021 - Virtual, Online
Duración: 27 sep 202129 sep 2021

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen13004 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia12th International Conference on Computational Logistics, ICCL 2021
CiudadVirtual, Online
Período27/09/2129/09/21

Nota bibliográfica

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

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