Ali Jahed, Seyyed Mohammad Hadji Molana, Reza Tavakkoli-Moghaddam, Vahideh Valizadeh
{"title":"设计具有可持续复原能力的综合混配疫苗供应链网络","authors":"Ali Jahed, Seyyed Mohammad Hadji Molana, Reza Tavakkoli-Moghaddam, Vahideh Valizadeh","doi":"10.1007/s10479-024-06211-1","DOIUrl":null,"url":null,"abstract":"<p>Vaccination is the most effective strategy for battling infectious diseases, breaking the disease transmission chain, and achieving herd immunity. Implementing vaccination for the whole population requires an integrated vaccine supply chain network that considers sustainability and resiliency in the network. For this purpose, in this research, a location-allocation-inventory-distribution problem in the sustainable and resilient vaccine supply chain network, considering mix-and-match vaccine regimens against SARS-CoV-2, is designed. The mix-and-match-based vaccination to reach robust immunization, increase vaccination effectiveness, and more resilience to cope with shortages is applied. In addition, three pillars of sustainability, to minimize distribution network costs, vaccine disposal impact, and greenhouse gas emissions, in terms of economic and environmental, and maximizing job creation, demand satisfaction, and vaccination effectiveness to ensure social sustainability, are developed. Also, scenario-based optimization is presented to meet the inevitable disruptions and breakdowns, such as the supply capacity of suppliers and uncertain amounts of vaccine demand, which depends on the previous type of vaccine injected, and robust stochastic programming is used to handle uncertainties. To solve the proposed model, efficient meta-heuristic algorithms, including the genetic algorithm (GA) and variable neighborhood search (VNS), are applied. In addition, a new hybrid algorithm called H-GAVNS based on the GA and VNS is developed in this research to discover near-optimal results. Finally, a case study of the COVID-19 vaccine in Iran’s environment is presented to confirm the accuracy of the presented model. The outcomes show that uncertainties in the real world and sustainability and resiliency aspects are well managed and responded to by the designed model.</p>","PeriodicalId":8215,"journal":{"name":"Annals of Operations Research","volume":"41 1","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Designing an integrated sustainable-resilient mix-and-match vaccine supply chain network\",\"authors\":\"Ali Jahed, Seyyed Mohammad Hadji Molana, Reza Tavakkoli-Moghaddam, Vahideh Valizadeh\",\"doi\":\"10.1007/s10479-024-06211-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Vaccination is the most effective strategy for battling infectious diseases, breaking the disease transmission chain, and achieving herd immunity. Implementing vaccination for the whole population requires an integrated vaccine supply chain network that considers sustainability and resiliency in the network. For this purpose, in this research, a location-allocation-inventory-distribution problem in the sustainable and resilient vaccine supply chain network, considering mix-and-match vaccine regimens against SARS-CoV-2, is designed. The mix-and-match-based vaccination to reach robust immunization, increase vaccination effectiveness, and more resilience to cope with shortages is applied. In addition, three pillars of sustainability, to minimize distribution network costs, vaccine disposal impact, and greenhouse gas emissions, in terms of economic and environmental, and maximizing job creation, demand satisfaction, and vaccination effectiveness to ensure social sustainability, are developed. Also, scenario-based optimization is presented to meet the inevitable disruptions and breakdowns, such as the supply capacity of suppliers and uncertain amounts of vaccine demand, which depends on the previous type of vaccine injected, and robust stochastic programming is used to handle uncertainties. To solve the proposed model, efficient meta-heuristic algorithms, including the genetic algorithm (GA) and variable neighborhood search (VNS), are applied. In addition, a new hybrid algorithm called H-GAVNS based on the GA and VNS is developed in this research to discover near-optimal results. Finally, a case study of the COVID-19 vaccine in Iran’s environment is presented to confirm the accuracy of the presented model. The outcomes show that uncertainties in the real world and sustainability and resiliency aspects are well managed and responded to by the designed model.</p>\",\"PeriodicalId\":8215,\"journal\":{\"name\":\"Annals of Operations Research\",\"volume\":\"41 1\",\"pages\":\"\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2024-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Operations Research\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1007/s10479-024-06211-1\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Operations Research","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s10479-024-06211-1","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
Designing an integrated sustainable-resilient mix-and-match vaccine supply chain network
Vaccination is the most effective strategy for battling infectious diseases, breaking the disease transmission chain, and achieving herd immunity. Implementing vaccination for the whole population requires an integrated vaccine supply chain network that considers sustainability and resiliency in the network. For this purpose, in this research, a location-allocation-inventory-distribution problem in the sustainable and resilient vaccine supply chain network, considering mix-and-match vaccine regimens against SARS-CoV-2, is designed. The mix-and-match-based vaccination to reach robust immunization, increase vaccination effectiveness, and more resilience to cope with shortages is applied. In addition, three pillars of sustainability, to minimize distribution network costs, vaccine disposal impact, and greenhouse gas emissions, in terms of economic and environmental, and maximizing job creation, demand satisfaction, and vaccination effectiveness to ensure social sustainability, are developed. Also, scenario-based optimization is presented to meet the inevitable disruptions and breakdowns, such as the supply capacity of suppliers and uncertain amounts of vaccine demand, which depends on the previous type of vaccine injected, and robust stochastic programming is used to handle uncertainties. To solve the proposed model, efficient meta-heuristic algorithms, including the genetic algorithm (GA) and variable neighborhood search (VNS), are applied. In addition, a new hybrid algorithm called H-GAVNS based on the GA and VNS is developed in this research to discover near-optimal results. Finally, a case study of the COVID-19 vaccine in Iran’s environment is presented to confirm the accuracy of the presented model. The outcomes show that uncertainties in the real world and sustainability and resiliency aspects are well managed and responded to by the designed model.
期刊介绍:
The Annals of Operations Research publishes peer-reviewed original articles dealing with key aspects of operations research, including theory, practice, and computation. The journal publishes full-length research articles, short notes, expositions and surveys, reports on computational studies, and case studies that present new and innovative practical applications.
In addition to regular issues, the journal publishes periodic special volumes that focus on defined fields of operations research, ranging from the highly theoretical to the algorithmic and the applied. These volumes have one or more Guest Editors who are responsible for collecting the papers and overseeing the refereeing process.