Order Batching Problem in O2O Supermarkets

Kewei Zhou, Kexin Gao and Shandong Mou ()
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Kewei Zhou: Central University of Finance and Economics
Kexin Gao: Central University of Finance and Economics
Shandong Mou: Central University of Finance and Economics

A chapter in AI and Analytics for Smart Cities and Service Systems, 2021, pp 286-299 from Springer

Abstract: Abstract With the development of omni-channel retailing, the O2O retailing combining traditional offline with online channels brings both opportunities and challenges to conventional supermarkets. As an important factor for supermarkets’ online service capabilities, order picking has become a critical point for the survival and development of O2O supermarkets. Thus, how to fulfil customer orders efficiently as well as accurately has become an urgent problem. In order to improve the order fulfilment performance of O2O supermarkets, we build an order batching mathematical model which aims at minimising the total Late Finish Time (LFT). A genetic algorithm is applied to solve this model. By analysing extensive numerical experiment outputs, we discuss the influences of SKU concentration of online customer orders, the mean and variance of Maximum Allowable Completion Time (MACT) on the performance of order batching and tardiness. Besides, the Degree of Congestion (DOC) which reflects the potential conflict between online order fulfilment and offline customer shopping is particularly discussed. We lastly provide managerial insights and some practical recommendations for O2O supermarkets.

Keywords: O2O supermarket; Order picking problem; In-store order fulfilment; Omni-channel retailing (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnopch:978-3-030-90275-9_24

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DOI: 10.1007/978-3-030-90275-9_24

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