Procuring healthful blood products is essential to improve the therapy and increase the safety of patients.The use of blood and its products in cases of severe bleeding, surgical procedures and the treatment of various diseases. Another critical issue in using this valuable product is the emergence of crises such as earthquakes, in which a large number of injured people suffer severe bleeding and burns, leading to a sudden increase in the demand for blood products in the early days of the crisis. In order to increase the quality and safety of services for blood supply, two groups of donors, the whole blood and apheresis donation, have been considered, as well as the blood transfusion matrix has been used for adaptation between blood groups. To manage, isolate and categorize the wounded of these widespread disasters in order to receive medical and therapeutic services, the triage system has been used with due consideration to the severity of the injuries and the urgency of the need for treatment. This study proposes a bi-objective mixed-integer linear programming model for multi-period multi-product optimization of integrated blood supply chain network. Due to Dealing with the epistemic uncertainty of some critical parameters, Robust possibilistic programming models are tailored. The applicability and performance of these proposed models and validate them are studied in a real case study of the Tehran blood network. Keywords: Blood Supply Chain, Earthquake Disaster, ABO-Rh Matching Rules, Triage System, Uncertainty, Robust Possibilistic Programming Models
