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

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