A heuristic approach for the online order batching problem with multiple pickers
Date
2021
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
URL external
item.page.doi
Abstract
The Online Order Batching Problem with Multiple Pickers (OOBPMP) consists of optimizing the operations related to the picking process of orders in a warehouse, when the picking policy follows an order batching strategy. In this case, this variant of the well-known Order Batching Problem considers the existence of multiple workers in the warehouse and an online arrival of the orders. We study three different objective functions for the problem: minimizing the completion time, minimizing the picking time, and minimizing the differences in the workload among the pickers. We have identified and classified all previous works in the literature for the OOBPMP. Finally, we propose a multistart procedure hybridized with a Variable Neighborhood Descent metaheuristic to handle the problem. We test our proposal over well-known instances previously reported in the literature by empirically comparing the performance of our proposal with previous methods in the state of the art. The statistical tests corroborated the significance of the results obtained.
Description
S0360835221004216
Citation
Sergio Gil-Borrás, Eduardo G. Pardo, Antonio Alonso-Ayuso, Abraham Duarte, A heuristic approach for the online order batching problem with multiple pickers, Computers & Industrial Engineering, Volume 160, 2021, 107517, ISSN 0360-8352, https://doi.org/10.1016/j.cie.2021.107517
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item.page.licenceAtribución 4.0 Internacional