A data-driven picking strategy for micro fulfilment centers in quick commerce: the case of Korea
DOI: https://doi.org/10.3846/transport.2026.26098Abstract
Quick Commerce (Q-Commerce) allows customers to receive their orders from near Micro Fulfilment Centers (MFCs) in a short time. However, the fulfilment centers are difficult to maintain responsive and reliable delivery services with traditional Single Order Picking (SOP) systems. Motivated by the above challenge, this study develops a hybrid picking method for an order fulfilment center of a Korean delivery company. The hybrid method considers certain rules for order batching to complement a SOP method. The order batching rules enable pickers to deal with 2 customer orders within a specific range of order lines. The order picking development are based on the results of a Warehouse Activity Profiling (WAP) analysis. This analysis shows possible approaches for the development of the hybrid method by considering arrival rates of customer orders and their variability in terms of item type and quantity. Afterwards, the hybrid method is validated with an agent-based simulation model using actual order information of the case study company. This study finds that the hybrid method shows consistent performance in terms of order picking and fulfilment times under wide ranges of order arrival rate and variability.
Keywords:
online batch picking, single order picking, warehouse activity profiling, agent-based simulation, quick commerceHow to Cite
Share
License
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Alipour, M.; Mehrjedrdi, Y. Z.; Mostafaeipour, A. 2020. A rule-based heuristic algorithm for on-line order batching and scheduling in an order picking warehouse with multiple pickers, RAIRO – Operations Research 54(1): 101–107. https://doi.org/10.1051/ro/2018069
Cano, J. A.; Correa-Espinal, A. A.; Gómez-Montoya, R. A. 2018. A review of research trends in order batching, sequencing and picker routing problems, Revista Espacios 39(4): 18390403. Available from Internet: https://www.revistaespacios.com/a18v39n04/18390403.html
Cergibozan, Ç.; Tasan, A. S. 2019. Order batching operations: an overview of classification, solution techniques, and future research, Journal of Intelligent Manufacturing 30(1): 335–349. https://doi.org/10.1007/s10845-016-1248-4
Chen, F.; Wei, Y.; Wang, H. 2018. A heuristic based batching and assigning method for online customer orders, Flexible Services and Manufacturing Journal 30(4): 640–685. https://doi.org/10.1007/s10696-017-9277-7
Chen, M.-C.; Wu, H.-P. 2005. An association-based clustering approach to order batching considering customer demand patterns, Omega 33(4): 333–343. https://doi.org/10.1016/j.omega.2004.05.003
Chen, T.-L.; Cheng, C.-Y.; Chen, Y.-Y.; Chan, L.-K. 2015. An efficient hybrid algorithm for integrated order batching, sequencing and routing problem, International Journal of Production Economics 159: 158–167. https://doi.org/10.1016/j.ijpe.2014.09.029
De Koster, R.; Le-Duc, T.; Roodbergen, K. J. 2007. Design and control of warehouse order picking: a literature review, European Journal of Operational Research 182(2): 481–501. https://doi.org/10.1016/j.ejor.2006.07.009
Frazelle, E. 2001. World-Class Warehousing and Material Handling. McGraw-Hill Education. 256 p.
Giannikas, V.; Lu, W.; Robertson, B.; McFarlane, D. 2017. An interventionist strategy for warehouse order picking: evidence from two case studies, International Journal of Production Economics 189: 63–76. https://doi.org/10.1016/j.ijpe.2017.04.002
Gil-Borrás, S.; Pardo, E. G.; Alonso-Ayuso, A.; Duarte, A. 2021. A heuristic approach for the online order batching problem with multiple pickers, Computers & Industrial Engineering 160: 107517. https://doi.org/10.1016/j.cie.2021.107517
Grosse, E. H.; Glock, C. H.; Neumann, W. P. 2017. Human factors in order picking: a content analysis of the literature, International Journal of Production Research 55(5): 1260–1276. https://doi.org/10.1080/00207543.2016.1186296
Gu, J.; Goetschalckx, M.; McGinnis, L. F. 2007. Research on warehouse operation: a comprehensive review, European Journal of Operational Research 177(1): 1–21. https://doi.org/10.1016/j.ejor.2006.02.025
Henn, S. 2012. Algorithms for on-line order batching in an order picking warehouse, Computers & Operations Research 39(11): 2549–2563. https://doi.org/10.1016/j.cor.2011.12.019
Hossein Nia Shavaki, F.; Jolai, F. 2021. A rule-based heuristic algorithm for joint order batching and delivery planning of online retailers with multiple order pickers, Applied Intelligence 51: 3917–3935. https://doi.org/10.1007/s10489-020-01843-9
Lange, N. 2020. Quick Commerce – the Next Generation of E-Commerce. Available from Internet: https://www.nickilange.com/journal/2020/4/28/quick-commerce-the-next-generation-of-e-commerce
Li, J.; Huang, R.; Dai, J. B. 2017. Joint optimisation of order batching and picker routing in the online retailer′s warehouse in China, International Journal of Production Research 55(2): 447–461. https://doi.org/10.1080/00207543.2016.1187313
Ou, X. 2025. E-commerce in South Korea – Statistics & Facts. Available from Internet: https://www.statista.com/topics/2529/e-commerce-in-south-korea
Park, B. C. 2011. Order picking performance: strategies, issues, and measures, Journal of the Korean Institute of Industrial Engineers 37(4): 271–278.
Pérez-Rodríguez, R.; Hernández-Aguirre, A.; Jöns, S. 2015. A continuous estimation of distribution algorithm for the online order-batching problem, The International Journal of Advanced Manufacturing Technology 79(1–4): 569–588. https://doi.org/10.1007/s00170-015-6835-6
Pyle, E.; Zanetti, G. 2021. Current data processing strategies for cryo-electron tomography and subtomogram averaging, Biochemical Journal 478(10): 1827–1845. https://doi.org/10.1042/BCJ20200715
Van Nieuwenhuyse, I.; De Koster, R. B. M. 2009. Evaluating order throughput time in 2-block warehouses with time window batching, International Journal of Production Economics 121(2): 654–664. https://doi.org/10.1016/j.ijpe.2009.01.013
Xu, X.; Liu, T.; Li, K.; Dong, W. 2014. Evaluating order throughput time with variable time window batching, International Journal of Production Research 52(8): 2232–2242. https://doi.org/10.1080/00207543.2013.849009
Zhang, J.; Wang, X.; Chan, F. T. S.; Ruan, J. 2017. On-line order batching and sequencing problem with multiple pickers: a hybrid rule-based algorithm, Applied Mathematical Modelling 45: 271–284. https://doi.org/10.1016/j.apm.2016.12.012
Zhang, J.; Wang, X.; Huang, K. 2016. Integrated on-line scheduling of order batching and delivery under B2C e-commerce, Computers & Industrial Engineering 94: 280–289. https://doi.org/10.1016/j.cie.2016.02.001
Zhang, J.; Wang, X.; Huang, K. 2018. On-line scheduling of order picking and delivery with multiple zones and limited vehicle capacity, Omega 79: 104–115. https://doi.org/10.1016/j.omega.2017.08.004
View article in other formats
CrossMark check
Published
Issue
Section
Copyright
Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University.
License
This work is licensed under a Creative Commons Attribution 4.0 International License.