Trolley line picking: storage assignment and order sequencing to increase picking performance

David Füßler (), Nils Boysen () and Konrad Stephan ()
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David Füßler: Friedrich-Schiller-Universität Jena
Nils Boysen: Friedrich-Schiller-Universität Jena
Konrad Stephan: Friedrich-Schiller-Universität Jena

OR Spectrum: Quantitative Approaches in Management, 2019, vol. 41, issue 4, No 8, 1087-1121

Abstract: Abstract Trolley line picking is a special warehousing system particularly suited to fulfill high-volume demands for heavy stock keeping units (SKUs). In such a system, unit loads of SKUs are positioned along a given path passed by automated trolleys, i.e., carriers hanging from a monorail or automated guided vehicles. Once a trolley reaches a requested SKU, it automatically stops and announces the requested items on a display. This is the signal for an accompanying human picker to put the demanded items onto the trolley. In this way, picking continues until, at the end of the path, the current picking order is complete and the trolley moves onward to the shipping area. Meanwhile, the picker rushes back to meet the subsequent trolley associated with the next picking order. The picking performance of the trolley line system is mainly influenced by the picker’s unproductive walking from SKU to SKU during order processing and back to the next trolley when switching to the next order. In this paper, we investigate how the storage assignment of SKUs along the path and the order sequence influence picking performance. Specifically, we explore the positive effect of duplicating SKUs and storing them at multiple positions along the path. We formulate the interdependent storage assignment and order sequencing problems and introduce a decomposition heuristic. Our computational study investigates the solution performance of this procedure and shows that SKU duplication can considerably improve picking performance.

Keywords: Warehousing; Trolley line picking; Order fulfillment; Scheduling (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s00291-019-00566-9

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