Reducing Risks During Natural Disasters With Optimal Resource Allocation By Multi-Agent Optimization

Abstract

Natural disasters are notable for the high costs associated with responding to and recovering from them. In this paper we address the issue of critical resources allocation during natural disaster, that incorporates the level of importance of the effected region and cost parameter. Our risk reducing model can be applied to online stochastic environments in the domain of natural disasters. The framework achieves more efficient resource allocation in response to dynamic events and is applicable to problems where disaster evolves alongside the response efforts.