Operational workload balancing in manual order picking. (March 2020)

• Record Type: Journal Article
• Authors: Vanheusden, Sarah; van Gils, Teun; Caris, An; Ramaekers, Katrien; Braekers, Kris
• Is Part Of: Computers & industrial engineering. Volume 141(2020)
• Publication Date: 2020-03
• Subjects: Warehouse management -- Workload balancing -- Zone picking -- Meta-heuristic; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2020.106269
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: This paper shows the importance of daily workload balancing in manual order picking. Iterated local search algorithm to solve the problem efficiently. Real-life case to show performance benefits of daily workload balancing. A balanced pick schedule supports the manpower allocation process. A balanced pick schedule discovers bottlenecks in the order pick process. Abstract: A growing e-commerce market and increasing customer requirements put extra pressure on order picking operations. Collecting large quantities of relative small orders within limited time windows makes workload balancing in order picking a challenging and complicated task. Therefore, warehouse managers experience difficulties in balancing the daily workload of order pickers in every pick zone. This paper introduces the operational workload balancing problem within the domain of order picking. A mathematical model is introduced to describe the new order picking planning problem. Furthermore, an iterated local search algorithm is developed to solve the operational workload balancing problem efficiently and effectively. The benefits of daily workload balancing in order picking operations are analysed by means of a real-life case.