Platelet inventory management with demand and supply uncertainty and variable pricing considerations

Area of Science:

• Operations Research
• Healthcare Management
• Supply Chain Optimization

Background:

• Effective blood inventory management is critical for patient care.
• Blood products, like platelets, have unique challenges including perishability and unpredictable supply/demand.
• Existing models often overlook variable pricing and supply chain uncertainties.

Purpose of the Study:

• To develop a stochastic optimization model for hospital platelet inventory.
• To minimize costs by accounting for fluctuating prices and uncertain supply/demand.
• To address literature gaps in dynamic blood supply chain management.

Main Methods:

• A stochastic multi-period mixed integer linear programming (MILP) model was formulated.
• The model incorporates variable pricing linked to blood center supply.
• Discrete scenarios were used to represent uncertainties in supply and demand.

Main Results:

• The proposed model demonstrated a reduction in inventory costs.
• The optimization approach proved effective in managing platelet inventory under uncertainty.
• Results suggest the model's viability for practical hospital inventory planning.

Conclusions:

• The stochastic MILP model offers an improved approach to hospital blood inventory management.
• Accounting for price variability and supply chain uncertainties is crucial for cost reduction.
• This research provides a valuable tool for optimizing perishable inventory in healthcare settings.