Reliability and Maintenance Data Set for Resilience Optimization

This is a dataset with component reliability data, maintenance data, repaircrew data, routing distances for the following paper submitted to RESS for potential publication.
Ryan O’Neil, Claver Diallo, Abdelhakim Khatab, Nidhal Rezg (2024). Enhancing Critical Network Infrastructure Resilience Through Optimal Post-Disruption Maintenance and Routing Decisions, submitted to Reliability Engineering and System Safety, Elsevier.

This data is for experiment 4 in the paper. This set of experiments considers the network displayed in Figure 18, which includes a known source node s, sink node t, and multiple transshipment nodes. The arc index and capacity (in cubic meters per day, CMD) are indicated on each network arc. The network comprises a total of 31 components/arcs. When all components are functioning, the maximum achievable network flow is 112 CMD. With a demand set at d = 112 CMD, there are S = 43 d-MCs.

本数据集包含组件可靠性数据、维护数据、维修队伍数据以及后续提交至RESS以供潜在发表的论文中所述网络的路径距离数据。论文作者为Ryan O’Neil、Claver Diallo、Abdelhakim Khatab和Nidhal Rezg（2024）。论文题目为《通过最优的灾后维护和路由决策提升关键网络基础设施的韧性》，已提交至《可靠性工程与系统安全》杂志，由Elsevier出版。此数据集旨在为论文中的实验4提供数据支持。实验系列考虑了图18中展示的网络，其中包含已知的源节点s、汇节点t以及多个中转节点。每个网络弧上均标明了弧索引和容量（以每日立方米计，简称CMD）。该网络由总计31个组件/弧组成。当所有组件均处于正常工作时，网络的最大可达流量为112 CMD。在设定需求为d = 112 CMD的情况下，存在S = 43个d-MCs。