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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/26047

Title: An Efficient Iterated Local Search Algorithm to Solve the Operational Workload Imbalance Problem
Authors: Vanheusden, Sarah
Van Gils, Teun
Braekers, Kris
Ramaekers, Katrien
Caris, An
Issue Date: 2018
Citation: 19th Free workshop in metaheuristics for industry: book of contributions,
Abstract: To stay competitive and preserve high service levels for customers, the focus of warehouses in today's supply chain is on fast and timely delivery of smaller and more frequent orders. To keep up with competitors, companies accept late orders from customers, which results in additional pressure for order picking operations. Specifically, more orders need to be picked and sorted in shorter and more flexible time windows, which often results in workload peaks during the day. The objective of this study is to formulate and solve the operational workload imbalance problem in parallel zone order picking systems. An iterated local search algorithm is provided to solve the planning problem. Solving the operational workload imbalance problem results in a more stable order picking process and overall productivity improvements for the total warehouse operations.
URI: http://hdl.handle.net/1942/26047
Link to publication: https://sites.google.com/view/eume2018/book-of-contributions
Category: C2
Type: Proceedings Paper
Appears in Collections: Research publications

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Supplementary material - reviewer 155.69 kBAdobe PDF
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