备灾
自然灾害
应急响应
准备
启发式
应急管理
运筹学
计算机科学
事件(粒子物理)
比例(比率)
灾害应对
工程类
地理
医疗急救
人工智能
气象学
医学
物理
地图学
量子力学
政治学
法学
作者
Carmen G. Rawls,Mark A. Turnquist
标识
DOI:10.1016/j.trb.2009.08.003
摘要
Pre-positioning of emergency supplies is one mechanism of increasing preparedness for natural disasters. The goal of this research is to develop an emergency response planning tool that determines the location and quantities of various types of emergency supplies to be pre-positioned, under uncertainty about if, or where, a natural disaster will occur. The paper presents a two-stage stochastic mixed integer program (SMIP) that provides an emergency response pre-positioning strategy for hurricanes or other disaster threats. The SMIP is a robust model that considers uncertainty in demand for the stocked supplies as well as uncertainty regarding transportation network availability after an event. Due to the computational complexity of the problem, a heuristic algorithm referred to as the Lagrangian L-shaped method (LLSM) is developed to solve large-scale instances of the problem. A case study focused on hurricane threat in the Gulf Coast area of the US illustrates application of the model.
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