Convalescent plasma bank facility location-allocation problem for COVID-19.

Area of Science:

• Operations Research
• Healthcare Management
• Supply Chain Optimization

Background:

• Convalescent plasma is a key COVID-19 treatment, necessitating efficient supply chains.
• Limited supply and rising cases highlight the need for optimized plasma bank networks.
• Existing models may not fully address the stochastic nature and perishability of plasma.

Purpose of the Study:

• To develop a novel model for the location-allocation of convalescent plasma bank facilities.
• To optimize plasma collection facility placement for efficient network flow.
• To minimize plasma wastage by integrating a deterioration rate into the supply chain model.

Main Methods:

• Formulation of a robust mixed-integer linear programming (MILP) model.
• Inclusion of two conflicting objectives: minimizing transportation time and total supply chain cost (including inventory).
• Validation using Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) and a modified NSGA-III, solved via CPLEX.

Main Results:

• An optimized MILP model for plasma bank and collection facility location-allocation.
• Demonstrated reduction in plasma transportation time and supply chain costs.
• Quantified reduction in plasma wastage due to integrated inventory and deterioration considerations.

Conclusions:

• The proposed model provides a robust framework for optimizing convalescent plasma supply chains.
• The model offers valuable decision support for policymakers in managing plasma resources.
• Effective supply chain management is crucial for ensuring timely access to critical treatments like convalescent plasma.