Designing a robust integrated supply chain model for blood products in times of crisis and uncertainty using NSGA II and MOPSO algorithms

The field of blood supply chain has become one of the most important fields of research due to its significant importance in saving human lives. After an earthquake, a large number of injured people suffer from severe bleeding and burns that require blood transfusions as soon as possible; Therefore, proper management of the blood supply to the injured is important, and the slightest negligence will endanger human lives. In such a situation, providing assistance to the injured and those in need of blood is very important and the loss of life and losses due to anemia should be greatly reduced by responding to the demand in a timely manner. In the present paper, a two-objective mathematical model under crisis and uncertainty is presented. Due to the high level of uncertainty in the blood supply chain in critical situations and due to the nature of uncertain parameters, a robust planning approach has been used. Also, due to the NP-hard nature of the problem, NSGA II and MOPSO algorithms have been used. To evaluate the results of the model, a real case study in Tehran has been used and sensitivity analysis has been performed on important parameters of the model. Finally, the computational results indicate that the quality of the output solutions of the NSGA II algorithm is better than the MOPSO algorithm and solves the problems in less time; Therefore, the results indicate the stability of the answers of the studied algorithm.