The integrated orderline batching, batch scheduling, and picker routing problem with multiple pickers: the benefits of splitting customer orders

Mustapha Haouassi, Yannick Kergosien, Jorge E. Mendoza () and Louis-Martin Rousseau
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Mustapha Haouassi: Université de Tours, LIFAT EA 6300, CNRS, ROOT ERL CNRS 7002
Yannick Kergosien: Université de Tours, LIFAT EA 6300, CNRS, ROOT ERL CNRS 7002
Jorge E. Mendoza: HEC Montréal, CIRRELT
Louis-Martin Rousseau: Ecole Polytechnique de Montréal, CIRRELT

Flexible Services and Manufacturing Journal, 2022, vol. 34, issue 3, No 3, 614-645

Abstract: Abstract Fast delivery is one of the most popular services in e-commerce retail. It consists in shipping the items ordered on-line in short times. Customer orders in this segment come with deadlines, and respecting this latter is pivotal to ensure a high service quality. The most time-consuming process in the warehouse is order picking. It consists in regrouping orders into batches, assigning those batches to order pickers, sequencing the batches assigned to each order picker such that the orders deadlines are satisfied, and the picking time is minimized. To speed up the order picking operations, e-commerce warehouses implement new logistical practices. In this paper, we study the impact of splitting the orders (assigning the orderlines of an order to multiple pickers). We thus generalize the integrated orders batching, batch scheduling, and picker routing problem by allowing the orders splitting and propose a route first-schedule second heuristic to solve the problem. In the routing phase, the heuristic divides the orders into clusters and constructs the picking tours that retrieve the orderlines of each cluster using a split-based procedure. In the scheduling phase, the constructed tours are assigned to pickers such that the orders deadlines are satisfied using a constraint programming formulation. On a publicly available benchmark, we compare our results against a state-of-the-art iterated local search algorithm designed for the non-splitting version of the problem. Results show that splitting the customer orders using our algorithm reduces the picking time by 30% on average with a maximum reduction of 60%.

Keywords: Order picking; Splitting customer orders; Route first-schedule second heuristic; Hard due-dates (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10696-021-09425-8

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