Designing an integrated sustainable-resilient mix-and-match vaccine supply chain network

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dc.authorscopusidReza Tavakkoli Moghaddam / 57207533714
dc.authorwosidReza Tavakkoli Moghaddam / P-1948-2015
dc.contributor.authorJahed, Ali
dc.contributor.authorMolana, Seyyed Mohammad Hadji
dc.contributor.authorTavakkoli Moghaddam, Reza
dc.contributor.authorValizadeh, Vahideh
dc.date.accessioned2025-04-18T08:50:23Z
dc.date.available2025-04-18T08:50:23Z
dc.date.issued2024
dc.departmentİstinye Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Endüstri Mühendisliği Bölümü
dc.description.abstractVaccination 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. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
dc.identifier.citationJahed, A., Molana, S. M. H., Tavakkoli-Moghaddam, R., & Valizadeh, V. (2024). Designing an integrated sustainable-resilient mix-and-match vaccine supply chain network. Annals of Operations Research, 1-50.
dc.identifier.doi10.1007/s10479-024-06211-1
dc.identifier.issn02545330
dc.identifier.scopus2-s2.0-85201200096
dc.identifier.scopusqualityQ1
dc.identifier.urihttp://dx.doi.org/10.1007/s10479-024-06211-1
dc.identifier.urihttps://hdl.handle.net/20.500.12713/6624
dc.identifier.wosWOS:001290126400001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakScopus
dc.indekslendigikaynakWeb of Science
dc.institutionauthorTavakkoli Moghaddam, Reza
dc.institutionauthoridReza Tavakkoli Moghaddam / 0000-0002-6757-926X
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofAnnals of Operations Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectHybrid Meta-heuristic Algorithm
dc.subjectMix-and-match Vaccine
dc.subjectResiliency
dc.subjectRobust Stochastic Optimization
dc.subjectSustainability
dc.subjectVaccine Supply Chain
dc.titleDesigning an integrated sustainable-resilient mix-and-match vaccine supply chain network
dc.typeArticle

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