Blood supply chain network design with lateral freight: A robust possibilistic optimization model

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dc.authoridSimic, Vladimir/0000-0001-5709-3744
dc.authoridBacanin, Nebojsa/0000-0002-2062-924X
dc.authoridTirkolaee, Erfan Babaee/0000-0003-1664-9210
dc.authoridAla, Ali/0000-0003-4552-4732
dc.authorwosidSimic, Vladimir/B-8837-2011
dc.authorwosidBacanin, Nebojsa/L-5328-2019
dc.authorwosidTirkolaee, Erfan Babaee/U-3676-2017
dc.contributor.authorAla, Ali
dc.contributor.authorSimic, Vladimir
dc.contributor.authorBacanin, Nebojsa
dc.contributor.authorTirkolaee, Erfan Babaee
dc.date.accessioned2024-05-19T14:39:30Z
dc.date.available2024-05-19T14:39:30Z
dc.date.issued2024
dc.departmentİstinye Üniversitesien_US
dc.description.abstractThe blood supply chain stands out as a crucial component within a healthcare system, which can significantly improve efficiency and save the health system's costs. This paper presents a multi-objective blood supply chain network design problem that aims to reduce the cost of establishing fixed and temporary facilities, transferring blood products, and the amount of shortage. In order to address the shortfall and boost adaptability, lateral freight across hospitals is suggested due to the uncertainty in supply and demand. A novel robust possibilistic mixed-integer linear programming method is proposed in this work in order to deal with distribution and locational decisions. Two well-known solution approaches of lexicographic and Torabi-Hassini methods are then utilized to treat the multi-objectiveness of the robust possibilistic optimization model. Lateral freight between various blood supply chain demands significantly affects load balancing, declining both delivery time and costs. According to the obtained outcomes, the overall delivery time and total cost decrease by 10% and 15%, respectively. Moreover, it is revealed that the lexicographic approach outperforms the Torabi-Hassini method in this research.en_US
dc.identifier.doi10.1016/j.engappai.2024.108053
dc.identifier.issn0952-1976
dc.identifier.issn1873-6769
dc.identifier.scopus2-s2.0-85185567625en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org10.1016/j.engappai.2024.108053
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4793
dc.identifier.volume133en_US
dc.identifier.wosWOS:001186930000001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofEngineering Applications of Artificial Intelligenceen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectBlood Supply Chainen_US
dc.subjectHealthcare Operationsen_US
dc.subjectPossibilistic Optimizationen_US
dc.subjectRobustnessen_US
dc.subjectLateral Freighten_US
dc.subjectUncertaintyen_US
dc.subjectFuzzy Programmingen_US
dc.titleBlood supply chain network design with lateral freight: A robust possibilistic optimization modelen_US
dc.typeArticleen_US

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