Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24897
Title: Designing Efficient Order Picking Systems by Combining Planning Problems: State-of-the-art Classification and Review
Authors: VAN GILS, Teun 
RAMAEKERS, Katrien 
CARIS, An 
De Koster, René B.M.
Issue Date: 2018
Source: European journal of operational research, 267(1), p. 1-15
Abstract: Warehouses deliver labor-intensive services to customers. Underperformance may result in high costs and unsatisfied customer demand. New market developments force warehouses to handle a large number of orders within tight time windows. To cope with this, order picking operations need to be optimized by solving a wide range of planning problems. Optimizing order picking planning problems sequentially may yield a suboptimal overall warehouse performance. Still, previous warehouse planning reviews focus on individual planning problems. This literature review differs by investigating combinations of multiple order picking planning problems. A state-of-the-art review and classification of the scientific literature investigating combinations of tactical and operational order picking planning problems in picker-to-parts systems is presented with the aim of determining how planning problems are related. Furthermore, this literature review aims to find excellent policy combinations and to provide guidelines how warehouse managers can benefit from combining planning problems, in order to design efficient order picking systems and improve customer service. Combining multiple order picking planning problems results in substantial efficiency benefits, which are required to face new market developments.
Notes: van Gils, T (reprint author), Hasselt Univ, Res Grp Logist, Agoralaan Bldg D, B-3590 Diepenbeek, Belgium. teun.vangils@uhasselt.be
Keywords: logistics; order picking; planning problem interactions; joint optimization; literature review
Document URI: http://hdl.handle.net/1942/24897
ISSN: 0377-2217
e-ISSN: 1872-6860
DOI: 10.1016/j.ejor.2017.09.002
ISI #: 000424722300001
Rights: © 2017 Elsevier B.V. All rights reserved.
Category: A1
Type: Journal Contribution
Validations: ecoom 2019
Appears in Collections:Research publications

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