Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108844
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dc.contributorDepartment of Industrial and Systems Engineeringen_US
dc.creatorTsang, YPen_US
dc.creatorMa, Hen_US
dc.creatorTan, KHen_US
dc.creatorLee, CKMen_US
dc.date.accessioned2024-08-27T04:41:20Z-
dc.date.available2024-08-27T04:41:20Z-
dc.identifier.issn0254-5330en_US
dc.identifier.urihttp://hdl.handle.net/10397/108844-
dc.language.isoenen_US
dc.publisherSpringer New York LLCen_US
dc.rights© The Author(s) 2024en_US
dc.rightsThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.en_US
dc.rightsThe following publication Tsang, Y.P., Ma, H., Tan, K.H. et al. A joint sustainable order-packing vehicle routing optimisation for the cold chain e-fulfilment. Ann Oper Res (2024) is available at https://doi.org/10.1007/s10479-024-05949-y.en_US
dc.subjectCold chainen_US
dc.subjectE-fulfilmenten_US
dc.subjectLast mile deliveryen_US
dc.subjectOrder packingen_US
dc.subjectSustainabilityen_US
dc.titleA joint sustainable order-packing vehicle routing optimisation for the cold chain e-fulfilmenten_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.doi10.1007/s10479-024-05949-yen_US
dcterms.abstractDue to the new normal caused by the pandemic, consumer behaviour has now shifted to online shopping not only for general commodities but also for food and other perishable products. Therefore, e-commerce fulfilment is now integrated with cold chain capabilities to satisfy stringent requirements on time-criticality and product quality, leading to the concept of cold chain e-fulfilment. In the cold chain e-fulfilment process, perishable orders are packed in thermal packaging solutions and delivered to consumers before the quality preservation time window. To secure a sufficient time buffer during last mile delivery, excessive use of thermal packaging materials is applied, which creates an adverse environmental impact on our eco-system. Aligning with low-carbon business practices, this study proposes a novel joint optimization model, namely the Joint Optimization of Sustainable Order Packing and Multi-Temperature Delivery Problem (JOSOPMDP), for order packing and vehicle routing decisions, where the sustainable use of thermal packaging materials is promoted without negatively influencing product quality and customer satisfaction. To evaluate its viability and performance, three sets of computational experiments are subsequently conducted. It is found that the proposed model is feasible to strike a balance between order packing and vehicle routing decisions. Compared with the traditional strategy, the average total cost and satisfaction level are improved by 3.26% and 47.88%, respectively. Consequently, this research fosters sustainable thinking in the cold chain e-fulfilment process, minimizing environmental impact.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAnnals of operations research, Published: 06 April 2024, Latest articles, https://doi.org/10.1007/s10479-024-05949-yen_US
dcterms.isPartOfAnnals of operations researchen_US
dcterms.issued2024-
dc.identifier.scopus2-s2.0-85189372368-
dc.identifier.eissn1572-9338en_US
dc.description.validate202408 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_TA-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextLaboratory for Artificial Intelligence in Design, Hong Kong under the InnoHK Research Clusters, Hong Kong Special Administrative Region Governmenten_US
dc.description.pubStatusEarly releaseen_US
dc.description.TASpringer Nature (2024)en_US
dc.description.oaCategoryTAen_US
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