School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran
Background and Objectives: A sudden jump in blood demand during natural disasters may have strong negative impact on the performance of blood supply chain. Appropriate response to emergency situations requires predictive approach to determining the optimal allocation of blood supply chain resources for various disaster scenarios. The present study, thus, presents an optimization model aimed at decreasing blood shortage, blood wastage, and blood supply cost in emergency situations. Methods: This work is an extension of our previously introduced stochastic blood supply chain model, which was developed based on the Robust Optimization concept. The aim of this model is to determine the optimal number and service areas of the blood facilities under different disaster scenarios using mixed integer linear programming. While in our previous model, the capacity of blood facility center was assumed to be constant, in the present work, it is considered as an integer variable varying within a defined interval. The present model, hence, allows exploring the influence of capacity of temporary facilities on the total costs of blood supply chain. Findings: Changing the capacity of mobile units from 80 to 120 resulted in roughly 10% reduction in the costs, 20% reduction in the optimal number of fixed blood facilities, and 25% reduction in the optimal number of the required mobile blood facilities. Conclusions: While the results of model analysis predict a marginal impact of the capacity of mobile units on the total cost, the capacity of these units is anticipated to considerably influence the optimal number of both permanent and temporary facilities.