Resilience-Based Performance Modeling and Decision Optimization for Transportation Network

Zhang, Weili

Resilience-Based Performance Modeling and Decision Optimization for Transportation Network

dc.contributor.advisor	Nicholson, Charles
dc.contributor.author	Zhang, Weili
dc.contributor.committeeMember	Wang, Naiyu
dc.contributor.committeeMember	Ellingwood, Bruce
dc.contributor.committeeMember	Trafalis, Theodore
dc.contributor.committeeMember	González, Andrés
dc.date.accessioned	2017-12-13T21:37:24Z
dc.date.available	2017-12-13T21:37:24Z
dc.date.issued	2017-12-15
dc.date.manuscript	2017-12-08
dc.description.abstract	The economy and social well-being of a community heavily rely on the availability and functionality of its critical infrastructure systems, including power, water, gas, and transportation. Roadway networks are a fundamental component of transportation systems and, in the event of an extreme hazard, play a critical role during and after the event. Consequently, quantifying the performance of transportation infrastructures and optimizing decisions to mitigate, prepare for, respond to, and recover from the potential hazards. This research presented a novel resilience-based framework to support resilience planning regarding pre-disaster mitigation and post-disaster recovery. First, the author proposes a new performance metric for transportation network, weighted number of independent pathways (WIPW), integrating the network topology, redundancy level, traffic patterns, structural reliability of network components, and functionality of the network during community’s post-disaster recovery in a systematical way. To the best of our knowledge, WIPW is the only performance metric that permits risk mitigation alternatives for improving transportation network resilience to be compared on a common basis. Based on the WIPW, a decision methodology of prioritizing transportation network retrofit projects is developed. Second, our studies extend from pre-disaster mitigation to post-hazard recovery, i in which this research presents two metrics to evaluate the restoration over the horizon after disasters . That is, total recovery time and the skew of the recovery trajectory. Both metrics are involved in the multi-objective stochastic optimization problem of restoration scheduling. The metrics provided a new dimension to evaluate the relative efficiency of alternative network recovery strategies. The author then develops a restoration scheduling methodology for network post-disaster recovery that minimizes the overall network recovery time and optimizes the recovery trajectory, which ultimately will reduce economic losses due to network service disruption. The WIPW, pre-disaster mitigation, and post-disaster recovery are illustrated in the same hypothetical bridge network with 30 nodes and 37 bridges subjected to a scenario seismic event. Finally, a comprehensive stage-wise decision framework is introduced. The entire resilience planning is separated into three stages, pre-disaster mitigation, post-disaster emergency response, and long-term recovery. The WIPW is decomposed to three specific decision metrics to measure the performance of a network regarding robustness, redundancy, and recoverability, respectively. Decision support models for mitigation and recovery developed in the previous studies are revised to accommodate the stage-wise metrics. The proposed stage-wise framework is applied to a real-world roadway network of Shelby County, TN, USA subjected to seismic hazards.	en_US
dc.identifier.uri	https://hdl.handle.net/11244/52781
dc.language	en_US	en_US
dc.subject	Engineering, Industrial.	en_US
dc.subject	Resilience	en_US
dc.subject	Transportation network	en_US
dc.subject	Decision making	en_US
dc.thesis.degree	Ph.D.	en_US
dc.title	Resilience-Based Performance Modeling and Decision Optimization for Transportation Network	en_US
ou.group	College of Engineering::School of Industrial and Systems Engineering	en_US
shareok.orcid	0000-0002-3247-8872	en_US