Purpose: In this paper, a location-routing-allocation problem in a multi-objective blood supply chain network was designed to reduce the total cost of the supply chain network, the maximum unmet demand from distribution of goods, and decline greenhouse gas emissions due to the transport of goods among different levels of the network. The network levels considered for modeling include blood donation clusters, permanent and temporary blood transfusion centers, major laboratory centers and blood supply points. Other objectives included determining the optimal number and location of potential facilities, optimal allocation of the flow of goods between the selected facilities and determining the most suitable transport route to distribute the goods to customer areas in uncertainty conditions.
Methodology: Given that the model was NP-hard, the NSGA II and MOPSO algorithms were used to solve the model with a priority-based solution.
Findings: The results of the design of the experiments showed the high efficiency of the NSGA II algorithm in comparison with the MOPSO algorithm in finding efficient solutions.
Originality/Value: This study addresses the issue of blood perishability from blood sampling to distribution to customer demand areas
