Authors: Abderrahmen Bochenine, Ismail Almaraj

Published on: March 24, 2024

Impact Score: 7.8

Arxiv code: Arxiv:2403.16173

Summary

• What is new: This research introduces a new robust optimization approach for vaccine supply chain networks, accounting for multiple types of uncertainties and quality inspection errors.
• Why this is important: The complexity and uncertainty in vaccine supply chain networks, including demand fluctuations, inspection errors, vaccine waste, and defective treatment rate of vaccine waste.
• What the research proposes: A mixed integer linear programming model that optimizes the total cost of the supply chain, utilizing robust optimization to handle uncertainties.
• Results: Demonstrates the importance of considering different types of uncertainties in improving the overall objective function and provides managerial insights for vaccine supply chain optimization.

Technical Details

Technological frameworks used: Robust optimization approach

Models used: Mixed integer linear programming

Data used: Multi-product, multi-echelon, and multi-period vaccine supply chain data under uncertainty

Potential Impact

Healthcare logistics, supply chain management companies, vaccine manufacturers

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