Enhance picking viability in E-commerce warehouses under pandemic

Siqiang Guo, Manjeet Singh and Shadi Goodarzi

International Journal of Production Research, 2023, vol. 61, issue 15, 5302-5321

Abstract: The COVID-19 pandemic has caused critical challenges for e-commerce warehouses that strive to fulfill surging customer demand while facing a high virus infection risk. Current literature on picking optimization overlooks warehouse safety under pandemic conditions. Meanwhile, scattered storage and zone-wave-batch picking have been used in parallel by many large e-commerce warehouses, these two operational policies have not been considered together in picking optimization studies. This paper fills these gaps by solving an order batching problem considering scattered storage, zone-wave-batch picking, and pickers’ proximity simultaneously. We formulate and solve the mathematical model of the discussed problem and propose the Aisle-Based Constructive Batching Algorithm (ABCBA) to help warehouses pick more efficiently and safely. Experiments with extensive datasets from a major third-party logistics (3PL) company show that, compared to the current picking strategy, ABCBA can reduce the total picking time and the virus infection risk due to pickers’ proximity by 46% and 72%, respectively. Compared to other heuristics like tabu + nLSA3 (Yang, Zhao, and Guo 2020), ABCBA gets better results using less computation time.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2022.2101400 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:61:y:2023:i:15:p:5302-5321

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2022.2101400

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().