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首页> 外文期刊>Transportation Research Part B: Methodological >Optimal team deployment in urban search and rescue
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Optimal team deployment in urban search and rescue

机译：城市搜救中的最佳团队部署

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摘要

The problem of optimally deploying urban search and rescue (USAR) teams to disaster sites in post-disaster circumstances is formulated as a multistage stochastic program (MSP). A portion of sites requiring assistance arrive dynamically over the decision horizon and key problem characteristics are known only with uncertainty a priori. The problem seeks to identify a set of tours for USAR teams so as to maximize the total expected number of people that can be saved by attending to all or a subset of disaster sites within the disaster region. Decisions are taken dynamically over the decision horizon as situational awareness improves and survival likelihood diminishes with the aim of increasing the expected num-ber of saved lives. To overcome the expensive computational effort associated with solving a MSP, a column generation-based strategy that consists of solving a series of interrelated two-stage stochastic programs with recourse within a shrinking time horizon is developed.
机译：在灾后环境中将城市搜索救援队（USAR）最佳部署到灾难现场的问题被表述为多阶段随机计划（MSP）。需要帮助的站点的一部分在决策范围内动态到达，关键问题特征只有事先不确定才能知道。该问题旨在为USAR团队确定一组巡回演出，以便通过参加受灾地区内的全部或部分灾区来最大程度地节省预期的总人数。随着情境意识的提高和生存可能性的降低，动态地在决策范围内做出决策，以期增加预期的挽救生命数量。为了克服与解决MSP相关的昂贵的计算工作，开发了一种基于列生成的策略，该策略包括解决一系列相互关联的两阶段随机程序，并在缩小的时间范围内求助。

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