Robust Analysis of the Capacity of Mobile Units on Blood Supply Chain Performance

Document Type: Research Paper


School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran


Background and Objectives: Emergency situations like natural disaster, can affect the availability of sufficient blood supply when a sudden jump in blood demand betides. So designing the efficient blood supply chains, can perform effectively during and after emergency situations. This paper present an analysis on robust optimization model to decrease blood shortage, wastage and cost in each scenario that is possible to happen.
Methods: Jabbarzadeh et al. [9] have proposed a robust optimization model for blood supply chain network design under different disaster scenarios which the supply chain including blood centers, blood facilities and blood donors. In their model, blood facilities collecting blood from donors and send to blood centers. There are two kinds of blood facilities in the supply chain: i) permanent facility with large capacity which has fixed location in all period. ii) Temporary facilities with smaller capacity which can be located in different positions. For complete description of the model we refer reader to the original article. The present study is an extension to their model, which considers the capacity of temporary facilities belong to an interval and presents the analysis of the influence of temporary facilities capacity variations on blood supply chain cost.
Findings: By changing the capacity of mobile units between (-20%) and (+20%), the total cost will changes between (+3.67%) - (-5.64%). Also the optimal number of required fixed blood units varies between 10-8 units. Finally the optimal number of required mobile blood facilities change between 50 and 37 units.
Conclusions: Although the results show that the change in the capacity of mobile units will impact on the total cost, these changes are not considerable. However, this study shows that the capacity of mobile units significantly influence the optimal number of permanent and temporary facilities.