Two-stage stochastic formulation for relief operations with multiple agencies in simultaneous disasters.

Area of Science:

• Operations Research
• Disaster Management
• Stochastic Optimization

Background:

• Disasters cause increasing damage, challenging authorities, especially during simultaneous events.
• Uncertainty and multi-stakeholder collaboration complicate disaster relief efforts.
• Existing models lack formulations for simultaneous disasters involving multiple suppliers and agencies.

Purpose of the Study:

• To introduce a novel bi-objective, two-stage stochastic formulation for disaster preparedness and immediate response.
• To support integrated decision-making under uncertainty caused by simultaneous disasters.
• To address decisions involving multiple suppliers, agencies, and simultaneous disaster events.

Main Methods:

• Developed a bi-objective two-stage stochastic programming model.
• Incorporated decisions on supplier selection, facility location, agency involvement, and procurement.
• Tested the model using data from simultaneous hurricanes and storms in Mexico, 2013.

Main Results:

• Planning for multiple disasters reveals the true capacity of disaster response systems.
• Integrated decision-making demonstrates significant benefits compared to independent disaster planning.
• The model highlights the impact of agency deployment and the importance of human resources.

Conclusions:

• The proposed model effectively supports integrated decision-making for simultaneous disaster preparedness and response.
• Considering multiple stakeholders and uncertainties is crucial for effective disaster management.
• The study underscores the need for holistic planning that accounts for system boundaries and resource criticality.