A Framework to Robust Stochastic Optimization for Humanitarian Logistics

We propose a framework to robust stochastic optimization model for disaster management planning; in particular, we address making integrated decisions about the distribution of relief supplies and evacuation operations. Our decision-making approach recommends the best relief distribution centers to use as storage locations and determines their optimal inventory levels. The model also incorporates the priorities for the evacuation of particular communities, as well as specific disaster scenarios with estimates of the transportation needs and demand for aid. Our model attempts to minimize the sum of the expected value and the variance of the total cost of the relief chain. We present a case study that uses a flood hazard map and determines the distribution of aid for a flood emergency in Thailand.