Robust Box Approach for Blood Supply Chain Network Design under Uncertainty: Hybrid Moth-Flame Optimization and Genetic Algorithm

In this paper, a blood supply chain network (BSCN) is designed to reduce the total cost of under demand and transportation costs. The levels considered for modeling include donation clusters, permanent temporary transfusion centers, major laboratory centers points. Other goals included determining optimal number location potential facilities, allocation flow goods between selected facilities most suitable transport route distribute customer areas in uncertainty conditions. This study addresses issue prishability from sampling distribution areas. Given that model was NP-hard, MFGO algorithm were used solve with priority-based solution. results design experiments showed high efficiency comparison PSO finding efficient solutions. Also, mean objective function robust approach more than one deterministic approach, while standard deviation first less at all factor.