The problem of network design of blood supply chains is traditionally studied considering a maximum of three objective functions. In the real world, however, there are always many conflicting objectives for different stakeholders. This paper addresses a blood supply chain (BSC) network design problem to optimize the costs of blood shortage and substitution in addition to other common objective functions. To this end, four important objectives that decision makers are always faced with in disaster are considered: (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 known to be strongly NP-hard, the intelligent NSGA-II algorithm is applied to solve it in a reasonable time. Data from a real case study is used to evaluate the performance of the proposed solution method. The comparison of the results of the proposed algorithm with the mathematical model confirms the accuracy of the proposed method. Furthermore, the analysis of the results indicates the superiority of the proposed model over previous studies. Moreover, the proposed algorithm provides a wide range of suitable solutions. Therefore, different alternatives are presented to the decision makers to make a trade-off according to their preferences.
Stored only when both papers are in the corpus — 33 citations exist upstream.
Imported from OpenAlex (CC0) — nothing here is generated.