Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/108844
DC Field | Value | Language |
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dc.contributor | Department of Industrial and Systems Engineering | en_US |
dc.creator | Tsang, YP | en_US |
dc.creator | Ma, H | en_US |
dc.creator | Tan, KH | en_US |
dc.creator | Lee, CKM | en_US |
dc.date.accessioned | 2024-08-27T04:41:20Z | - |
dc.date.available | 2024-08-27T04:41:20Z | - |
dc.identifier.issn | 0254-5330 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/108844 | - |
dc.language.iso | en | en_US |
dc.publisher | Springer New York LLC | en_US |
dc.rights | © The Author(s) 2024 | en_US |
dc.rights | This 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.rights | The 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.subject | Cold chain | en_US |
dc.subject | E-fulfilment | en_US |
dc.subject | Last mile delivery | en_US |
dc.subject | Order packing | en_US |
dc.subject | Sustainability | en_US |
dc.title | A joint sustainable order-packing vehicle routing optimisation for the cold chain e-fulfilment | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.doi | 10.1007/s10479-024-05949-y | en_US |
dcterms.abstract | Due 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.accessRights | open access | en_US |
dcterms.bibliographicCitation | Annals of operations research, Published: 06 April 2024, Latest articles, https://doi.org/10.1007/s10479-024-05949-y | en_US |
dcterms.isPartOf | Annals of operations research | en_US |
dcterms.issued | 2024 | - |
dc.identifier.scopus | 2-s2.0-85189372368 | - |
dc.identifier.eissn | 1572-9338 | en_US |
dc.description.validate | 202408 bcch | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_TA | - |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | Laboratory for Artificial Intelligence in Design, Hong Kong under the InnoHK Research Clusters, Hong Kong Special Administrative Region Government | en_US |
dc.description.pubStatus | Early release | en_US |
dc.description.TA | Springer Nature (2024) | en_US |
dc.description.oaCategory | TA | en_US |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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s10479-024-05949-y.pdf | 1.52 MB | Adobe PDF | View/Open |
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