Resources allocation in disaster response using Ordinal Optimization based approach

Recent events, such as Hurricane Katrina, have revealed the need for coordinated and effective disaster responses. An optimal distribution of available resources is essential for disaster response effectiveness. Emergency responders are faced with the challenges of increased size and complexity of critical infrastructures that provide vital resources for disaster response operations. In this paper, we propose a simulation-based tool to assist emergency responders in finding the optimal distribution of available resources during a disaster event. The proposed tool utilizes the Disaster Response Network Enabled Platform (DR-NEP) which is an infrastructure interdependencies simulation platform for disaster response support. DR-NEP is a simulation network platform that integrates different simulators for different infrastructures to form a universal simulation platform. We employ a new concept in Discrete Event Systems optimization called Ordinal Optimization to address the problem of resources allocation during a disaster event. The objective of the optimization problem is maximizing the operational capacity of a critical infrastructure, a hospital in this case. Due to the huge combinatorial feasible search space, an Ordinal Optimization based approach is used to solve the problem using two main concepts: goal softening and order comparison. This approach aims at finding a Good Enough solution set (G) with an acceptable probability and efficient computational effort. This paper describes early results of our work that shows the use of our approach in optimizing resources allocation in a simulated disaster event.