Multi-objective optimization model for blood supply chain network design considering cost of shortage and substitution in disaster

The problem of blood supply chain network design is traditionally studied in considering a maximum of three objective functions. However, there are always many conflicting objectives for different stakeholders in the real world. This paper addresses a blood supply chain (BSC) network design problem to optimize the cost of blood shortage and substitution in addition to other common objective functions. To this end, four important objectives that decision-makers always are in the challenge in disaster are regarded as: (1) minimizing the total cost, (2) minimizing transportation time, (3) minimizing total unsatisfied demand, and (4) maximizing the total reliability. A mixed-integer linear programming (MIP) model is proposed to formulate the problem at hand. Since this problem is well-known strongly NP-hard, the intelligent NSGA-II algorithm is proposed and applied to solve this problem in a reasonable time. Data from a real case study is used to evaluate the performance of the proposed solution method. Comparison result to mathematical model (MIP) validates the performance accuracy and efficiency of the proposed method. In addition, the result demonstrates that the proposed algorithm performs better to solve the problem than the classic ones. The result analysis proves the proposed model and its superiority successfully compared to the previous studies. Moreover, the proposed algorithm can provide a broad range of proper solutions as different alternatives for decision-makers to make a trade-off according to their preferences