Ala, AliSimic, VladimirBacanin, NebojsaTirkolaee, Erfan Babaee2024-05-192024-05-1920240952-19761873-6769https://doi.org10.1016/j.engappai.2024.108053https://hdl.handle.net/20.500.12713/4793The 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.eninfo:eu-repo/semantics/closedAccessBlood Supply ChainHealthcare OperationsPossibilistic OptimizationRobustnessLateral FreightUncertaintyFuzzy ProgrammingArticle133WOS:0011869300000012-s2.0-85185567625N/A10.1016/j.engappai.2024.108053Q1