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Optimizing designs and operations of a single network or multiple interdependent infrastructures under stochastic arc disruption

机译:在随机电弧中断下优化单个网络或多个相互依赖的基础架构的设计和操作

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In this paper, we consider an infrastructure as a network with supply, transshipment, and demand nodes. A subset of potential arcs can be constructed between node pairs for conveying service flows. The paper studies two optimization models under stochastic arc disruption. Model 1 focuses on a single network with small-scale failures, and repairs arcs for quick service restoration. Model 2 considers multiple interdependent infrastructures under large-scale disruptions, and mitigates cascading failures by selectively disconnecting failed components. We formulate both models as scenario-based stochastic mixed-integer programs, in which the first-stage problem builds arcs, and the second-stage problem optimizes recourse operations for restoring service or mitigating losses. The goal is to minimize the total cost of infrastructure design and recovery operations. We develop cutting-plane algorithms and several heuristic approaches for solving the two models. Model 1 is tested on an IEEE 118-bus system. Model 2 is tested on systems consisting of the 118-bus system, a 20-node network, and/or a 50-node network, with randomly generated interdependency sets in three different topological forms (i.e., chain, tree, and cycle). The computational results demonstrate that (ⅰ) decomposition and cutting-plane algorithms effectively solve Model 1, and (ⅱ) heuristic approaches dramatically decrease the CPU time for Model 2, but yield worse bounds when cardinalities of interdependency sets increase. Future research includes developing special algorithms for optimizing Model 2 for complex multiple infrastructures with special topological forms of system interdependency.
机译:在本文中,我们将基础设施视为具有供应,转运和需求节点的网络。可以在节点对之间构造潜在电弧的子集,以传送服务流。本文研究了随机电弧扰动下的两种优化模型。模型1集中于一个具有小规模故障的单一网络,并修复电弧以快速恢复服务。模型2考虑了大规模中断下的多个相互依赖的基础架构,并通过有选择地断开故障组件的连接来减轻级联故障。我们将这两种模型都公式化为基于场景的随机混合整数程序,其中第一阶段的问题会建立弧线,第二阶段的问题会优化资源操作以恢复服务或减轻损失。目标是最大程度地减少基础结构设计和恢复操作的总成本。我们开发了切面算法和几种启发式方法来求解这两个模型。模型1在IEEE 118总线系统上进行了测试。在由118总线系统,20节点网络和/或50节点网络组成的系统上测试了模型2,该系统具有以三种不同拓扑形式(即链,树和循环)随机生成的相互依赖集。计算结果表明,(ⅰ)分解和切平面算法有效地解决了模型1,并且(ⅱ)启发式方法显着减少了模型2的CPU时间,但是当相互依赖集的基数增加时,边界会更差。未来的研究包括开发特殊算法,以优化具有系统相互依赖关系的特殊拓扑形式的复杂多个基础结构的模型2。

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