CENTRALIZED PLASMA SUPPLY CHAIN NETWORK DESIGN UNDER UNCERTAIN DONOR AND RECIPIENT AVAILABILITY

Abstract

The efficient management of the plasma supply chain network is a critical component of ensuring the availability of safe and healthy plasma units for transfusion. Plasma is an essential lifesaving component of blood and therefore plasma supply chain optimization plays a critical role in minimizing plasma waste and shortages at the time of need. In this research, a multi-objective linear programming (MOLP) model is developed for optimizing centralized plasma supply chain network design. The multifaceted challenges of network design are addressed by focusing on three key objectives: operational cost minimization, RFID-enabled traceability for healthy plasma units transfused, and the prioritization of blood type compatibility in plasma transfusion. Two-fold methodology has been employed for this study. Chance constraint programming has been implemented using the mean variance approach to mitigate the inherent uncertainty of demand and supply of plasma due to the voluntary-donations based supply chain. It not only optimizes the supply chain network but also ensures robustness by incorporating probabilistic constraints. This approach allows for the effective management of uncertain factors, contributing to a more reliable and cost-efficient supply chain. Furthermore, we introduce an interactive multi objective fuzzy programming technique to address the complexity of balancing the three objectives simultaneously. This approach facilitates decision-making by allowing for trade-offs and interactions among the objectives. To validate the proposed methodologies and their practical implications, a real-time case study is conducted within a region of a developing country. The findings of this study provide insights into the effectiveness of the developed models and offer actionable recommendations for improving the efficiency and resilience of the plasma supply chain The key outcomes of this research include the minimization of operational costs, the maximization of traceability, and the prioritization of blood type compatibility, in plasma transfusion. By integrating these objectives, our approach contributes to the optimization of the centralized plasma supply chain network and enhances the overall quality and safety of plasma transfusion processes