© 2024Blood plays a critical role in humanitarian logistics, and it is essential to create an appropriate blood type supply chain (BTSC) network to manage the supply and demand of blood components efficiently, especially during crises. This paper formulates a bi-objective model to minimize cost and blood shortage simultaneously. This study considers all essential aspects of the BTSC network, entailing the position of blood amenities, allocation of donors, as well as different facilities and blood centers, collection, production, and testing of perishable blood components of multiple blood types, uncertain demand, and more importantly, time-dependent routing decisions. Supply and demand uncertainties are considered in this study; a scenario-based two-stage stochastic programming is adopted to cope with the scenario-dependent variables, like blood allocation and routing selection after a disaster. The modified version of augmented ε-constraint 2 (AUGMECON2) is applied to solve the proposed model. Several numerical instances are applied to check the model and the suggested solution method’s accuracy, and a real case study is utilized to reveal the model’s applicability. Through solving the problem, the importance of several new ideas, such as blood types and novel type I regional blood centers (RBC) as well as time-dependent routing problem, has been highlighted. Finally, sensitivity analysis has been conducted to analyze the impacts of the significant parameters on the target functions; consequently, pertinent managerial insights are derived from sensitivity analysis.
https://doi.org/10.1016/j.cie.2024.109899Cite as:
@article{Entezari_2024, title={A Bi-objective stochastic blood type supply chain configuration and optimization considering time-dependent routing in post-disaster relief logistics}, volume={188}, ISSN={0360-8352}, url={http://dx.doi.org/10.1016/j.cie.2024.109899}, DOI={10.1016/j.cie.2024.109899}, journal={Computers & Industrial Engineering}, publisher={Elsevier BV}, author={Entezari, Sarah and Abdolazimi, Omid and Fakhrzad, Mohammad Bagher and Shishebori, Davood and Ma, Junfeng}, year={2024}, month=feb, pages={109899} }