blood and its products play an undeniable role in human life. In recent years, although both academics and practitioners have investigated blood-related problems, further enhancement is still warranted. In this study, a mixed-integer linear programming model was proposed for local blood supply chain management. A supply network, including temporary and fi xed blood donation facilities, blood banks, and blood processing centers, was designed regarding the deteriorating nature of blood. The proposed model was applied in a real case in Urmia, Iran. The numerical results and sensitivity analysis of the key model parameters ensured the applicability of the proposed model.

Ensuring an adequate and healthy blood supply is a persistent challenge that healthcare systems worldwide face. The need for blood donors and their products is constant, while the supply from donors is somewhat irregular, and the demand for these products is often unpredictable. Furthermore, the levels of demand and blood donation are uncertain. As a result, uncertainty plays a crucial role in the blood supply chain, especially during crises such as earthquakes and pandemics. In this regard, designing the  blood supply chain Network (BSCN) under uncertainty is essential for meeting fluctuating demand, addressing logistical challenges, responding to emergencies, and ensuring the quality and safety of blood products throughout the supply chain. This research aims to present a Mixed-Integer Linear Programming (MIP) model under uncertainty for strategic and tactical decision-making in the blood supply chain over a determined planning horizon. The fuzzy theory approach has been used to incorporate uncertainty into the model's parameters. An interactive fuzzy solution approach based on credibility measurement has been developed to solve the fuzzy optimization model. The results obtained from designing and implementing the proposed model in a case study indicate the desirable efficiency of this model in determining the optimal number and location of facilities in a BSCN, including fixed facilities, temporary facilities, and blood banks, as well as the optimal amount of blood transfer between different entities of the blood supply chain. Furthermore, a sensitivity analysis of the parameters is performed to determine the most influential factors affecting the objective function of the problem.

Management of the blood as a vital and scarce resource is very important. The aim of this research is to present a novel mathematical model for designing a reliable blood supply chain network. This network consists of three main echelons including donors, collection facilities and demand points. At the collection echelon, three types of facilities are considered for receiving the bloods from the donors: main blood centers (MBCs), demountable collection centers (DCCs), and mobile blood facilities (MBFs). DCCs, and MBFs are mobile facilities that don’t have a permanent location and always move from a location to another one for collecting the bloods from the donors. The main difference between the MBFs and DCCs is that the DCCs can only visit at most a candidate location every period, but the MBFs can visit more than one candidate location in every period. Also, there is differences between their capacities and their costs. Both of DCCs and MBFs dispatch the collected bloods to the MBCs that are permanent facilities and are responsible for receiving the bloods and performing the blood transfusion process and finally sending the bloods to the demand points. Using a numerical example, the applicability of the proposed network is analyzed.