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Optimizing infrastructure resilience under budgetary constraint

机译:在预算约束下优化基础架构的弹性

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Communities located in regions prone to natural and man-made disasters endure hardship and financial loss in the face of these events. Investment to enhance infrastructure resilience is vital to reduce the consequences of these low probability high-impact events. Budget and resources are limited, and they must be allocated wisely to infrastructure components to build a resilient community. The complexity of infrastructure makes it difficult to show the effects of component enhancements on system resilience. This paper proposes a mathematical programming model aimed at optimizing infrastructure resilience against a set of adverse events by optimally allocating budget to the infrastructure components. Investment, component enhancement, and corresponding functionality are combined with the resilience-based component importance to tackle the system complexity. Three utility functions are presented to determine the possible component enhancement alternatives for an allocated budget and to choose the optimal alternative. A resilience-based component importance metric is introduced, which is used in the budget allocation optimization problem. This approach establishes a relationship between amount allocated to a component and changes in its absorption and recovery, and the aggregate of all such changes on the components on the system functionality. The results show that the utility function of a component impacts the resilience enhancement of the system.
机译:面对这些自然灾害,位于容易遭受自然和人为灾难的地区的社区遭受苦难和财务损失。增强基础设施弹性的投资对于减少这些低概率高影响事件的后果至关重要。预算和资源是有限的,必须明智地将其分配给基础架构组件,以建立有弹性的社区。基础结构的复杂性使得很难显示组件增强对系统弹性的影响。本文提出了一种数学编程模型,旨在通过将预算最佳分配给基础架构组件来优化基础架构对一系列不利事件的适应力。投资,组件增强和相应的功能与基于弹性的组件重要性相结合,以解决系统复杂性。介绍了三个实用程序功能,以确定分配的预算的可能的组件增强替代方案并选择最佳替代方案。引入了基于弹性的组件重要性指标,该指标用于预算分配优化问题。这种方法在分配给组件的数量与其吸收和恢复的更改之间的关系以及系统功能上所有此类更改的总和之间建立了关系。结果表明,组件的效用函数会影响系统的弹性增强。

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