Bi-objective blood product scheduling under blood shortage and limited supply

Increased blood demand and limited supply make shortages a significant problem in the chain, which may cause immeasurable losses. The objective of this paper is to develop scheduling scheme products during shortages, considering supply. For purpose, bi-objective mixed-integer programming model proposed, one minimises maximum shortage hospitals as well other latest arrival time. To solve model, $ \varepsilon $-constraint-based hybrid algorithm called $-GA-VNS presented, benefits from exploration genetic (GA) exploitation variable neighbourhood search (VNS) approaches. Then, series numerical experiments based on Solomon's benchmark were performed evaluate proposed algorithm. A performance comparison NSGA-II indicated that was superior both efficiency effectiveness. Finally, sensitivity analyses uncertain stochastic impart several managerial insights.