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Pre-positioning disaster response facilities at safe locations: An evaluation of deterministic and stochastic modeling approaches

机译:将灾难响应设施预先放置在安全的位置:确定性和随机建模方法的评估

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Choosing the locations of disaster response facilities for the storage of emergency supplies is critical to the quality of service provided post-occurrence of a large scale emergency like an earthquake. In this paper, we provide two location models that explicitly take into consideration the impact a disaster can have on the disaster response facilities and the population centers in surrounding areas. The first model is a deterministic model that incorporates distance-dependent damages to disaster response facilities and population centers. The second model is a stochastic programming model that extends the first by directly considering the damage intensity as a random variable. For this second model we also develop a novel solution method based on Benders Decomposition that is generalizable to other 2-stage stochastic programming problems. We provide a detailed case study using large-scale emergencies caused by an earthquake in California to demonstrate the performance of these new models. We find that the locations suggested by the stochastic model in this paper significantly reduce the expected cost of providing supplies when one considers the damage a disaster causes to the disaster response facilities and areas near it. We also demonstrate that the cost advantage of the stochastic model over the deterministic model is especially large when only a few facilities can be placed. Thus, the value of the stochastic model is particularly great in realistic, budget-constrained situations. (C) 2014 Elsevier Ltd. All rights reserved.
机译:选择灾难应急设施的位置来存储应急物资,对于大规模地震(如地震)发生后提供的服务质量至关重要。在本文中,我们提供了两个位置模型,这些模型明确考虑了灾难可能对灾难响应设施和周围人口中心的影响。第一个模型是确定性模型,其中包含了对灾难响应设施和人口中心的距离相关损害。第二个模型是随机编程模型,通过直接将破坏强度视为随机变量来扩展第一个模型。对于第二个模型,我们还开发了一种基于Benders分解的新颖的求解方法,该方法可以推广到其他两阶段随机规划问题。我们提供了一个详细的案例研究,使用加利福尼亚地震造成的大规模紧急情况来说明这些新模型的性能。我们发现,当人们考虑灾难对灾难响应设施及其附近地区造成的破坏时,本文中的随机模型所建议的位置大大降低了预期的物资供应成本。我们还证明,当只能放置少量设施时,随机模型相对于确定性模型的成本优势特别大。因此,在现实,预算有限的情况下,随机模型的价值特别大。 (C)2014 Elsevier Ltd.保留所有权利。

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