Scenario-robust pre-disaster planning for multiple relief items.

Area of Science:

• Operations Research
• Supply Chain Management
• Disaster Management

Background:

• Increasing population vulnerability to frequent disasters necessitates efficient humanitarian supply chain (HSC) networks.
• Effective disaster response relies on timely distribution of relief items.

Purpose of the Study:

• To develop scenario-robust optimization models for strategic stocking of multiple disaster relief items.
• To enhance the robustness of solutions in disaster response planning by addressing uncertainty in parameters.

Main Methods:

• Development of scenario-robust optimization models.
• Utilizing distribution-free uncertainty sets (ranges) for uncertain parameters.
• Case study application for hurricane preparedness in the Southeastern United States.
• Simulation studies to validate model effectiveness under varying conditions.

Main Results:

• The proposed models improve the robustness of disaster relief supply chain solutions.
• The approach accommodates decision-makers' varying degrees of knowledge about uncertain parameters.
• Demonstrated applicability and effectiveness through a hurricane preparedness case study and simulations.

Conclusions:

• The developed models offer a flexible and robust framework for disaster relief supply chain optimization.
• This approach enhances preparedness and response capabilities for frequent and uncertain disaster events.
• The methodology provides a practical tool for decision-makers in humanitarian logistics.