2017
DOI: 10.1016/j.ijpe.2017.04.002
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An interventionist strategy for warehouse order picking: Evidence from two case studies

Abstract: As the role of the customer becomes more important in modern logistics, warehouses are required to improve their response to customer orders. To meet the responsiveness expected by customers, warehouses need to shorten completion times. In this paper, we introduce an interventionist order picking strategy that aims to improve the responsiveness of order picking systems. Unlike existing dynamic strategies, the proposed strategy allows a picker to be intervened during a pick cycle to consider new orders and oper… Show more

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Cited by 58 publications
(48 citation statements)
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“…Very different application cases are discussed in research approaches, from fruit picking in agriculture to online retail order picking in e-commerce. In general, the important message herein is the fact that individual product characteristics and requirements shape many of the typical design elements of order picking systems, especially the efficient level of automation [27][28][29][30][31][32][33][34][35].…”
Section: Theoretical Frameworkmentioning
confidence: 99%
“…Very different application cases are discussed in research approaches, from fruit picking in agriculture to online retail order picking in e-commerce. In general, the important message herein is the fact that individual product characteristics and requirements shape many of the typical design elements of order picking systems, especially the efficient level of automation [27][28][29][30][31][32][33][34][35].…”
Section: Theoretical Frameworkmentioning
confidence: 99%
“…By far, order picking is the area, where most research in terms of AR application in logistics can be found. Due to its operational complexity and economical relevance (more than 50% of warehousing costs incurred in picking area) [12], it is also the field where huge potential of process optimization in logistics exists. Previous research mainly focused on how an operator could be aided by using AR [13], what is the most effective way to indicate a storage location to a picker [14].…”
Section: Identification Of Ar Application In Inhouse Logisticsmentioning
confidence: 99%
“…In a dynamic order pick system, order throughput time is more convenient to evaluate performances. As in our case a non-dynamic order pick system is assumed and both performance measures are highly correlated, total order pick time is minimized in this study as this mostly results in the smallest order throughput time as well (Giannikas et al, 2017).…”
Section: Performance Measuresmentioning
confidence: 99%