Shan Qiao, Mingke He, Jing Wang, Jianping Cai, Jie Zheng
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We then transform it into a solvable robust counterpart model, propose a dynamic adjustment strategy, and cope with it using the Rolling Horizon approach to obtain dynamic location and materials distribution decisions. Finally, we conduct a case study of the Shanghai epidemic in 2022 to verify the feasibility and effectiveness of our model and method.KEYWORDS: Major infectious disease epidemicsmodified SEIR modelemergency materials supply chain networkrobust optimizationuncertain budget adjustmentrolling horizon approach Data availability statementThe data of this study are available upon request from the corresponding author.Disclosure statementNo potential conflict of interest was reported by the author(s).Ethics approvalThis article does not contain any studies with human participants or animals performed by any of the authors.Additional informationFundingThis work was supported by Key program of The National Social Science Fund of China [grant number 20AJY016].","PeriodicalId":14018,"journal":{"name":"International Journal of Logistics Research and Applications","volume":null,"pages":null},"PeriodicalIF":4.5000,"publicationDate":"2023-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust optimization for a dynamic emergency materials supply chain network under major infectious disease epidemics\",\"authors\":\"Shan Qiao, Mingke He, Jing Wang, Jianping Cai, Jie Zheng\",\"doi\":\"10.1080/13675567.2023.2269101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACTThe COVID-19 outbreak has posed serious challenges to logistics and supply chain management. 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Robust optimization for a dynamic emergency materials supply chain network under major infectious disease epidemics
ABSTRACTThe COVID-19 outbreak has posed serious challenges to logistics and supply chain management. This study examines how living materials can be provided to a population under quarantine control due to the spread of infectious diseases. First, we present a modified SEIR model for predicting the number of people and materials demanded. Considering the dynamic evolution and other characteristics of infectious diseases, and the resulting demand uncertainty, we develop a robust optimization model for a multi-period dynamic emergency materials supply chain network with the objective of minimising total cost. We then transform it into a solvable robust counterpart model, propose a dynamic adjustment strategy, and cope with it using the Rolling Horizon approach to obtain dynamic location and materials distribution decisions. Finally, we conduct a case study of the Shanghai epidemic in 2022 to verify the feasibility and effectiveness of our model and method.KEYWORDS: Major infectious disease epidemicsmodified SEIR modelemergency materials supply chain networkrobust optimizationuncertain budget adjustmentrolling horizon approach Data availability statementThe data of this study are available upon request from the corresponding author.Disclosure statementNo potential conflict of interest was reported by the author(s).Ethics approvalThis article does not contain any studies with human participants or animals performed by any of the authors.Additional informationFundingThis work was supported by Key program of The National Social Science Fund of China [grant number 20AJY016].
期刊介绍:
International Journal of Logistics: Research & Applications publishes original and challenging work that has a clear applicability to the business world. As a result the journal concentrates on papers of an academic journal standard but aimed at the practitioner as much as the academic. High quality contributions are therefore welcomed from both academics and professionals working in the field of logistics and supply chain management. Papers should further our understanding of logistics and supply chain management and make a significant original contribution to knowledge. In this context the term "logistics" is taken in its broadest context as "the management of processes, flow of materials and associated information along the entire supply chain.