Analysis and operations in complex networked systems: From urban infrastructure to epidemics

Many real-world systems run with underlying complex networked structures, and system disruptions or signals of many sorts are transmitted along these networks. This dissertation aims at investigating the dynamics and operations in different types of complex networked systems, with two main focuses: i) infrastructure cascading failures in urban interdependent infrastructure networks, and ii) infectious disease propagation dynamics and control in population contact networks. Under each topic, one or several studies are performed with different focuses to reveal insights on varies aspects of the real-world networked systems, and provide decision-making frameworks to operational problems. First, in an urban infrastructure system, local disruptions are likely to propagate to affect a large fraction of the system due to high infrastructural interdependencies. Meanwhile, urban population's response to the disruptions may further aggravate the cascading failures when they compete with facilities for limited resources. To capture the mutual impacts between infrastructural interdependencies and population behavior, a generic game-theoretical framework is built to find the overall equilibrium among the system. Infrastructure systems are modeled as layers of interdependent networks. Infrastructural interdependencies are captured by both direct support relationships as well as indirect support via commodity flows through transportation. On the other hand, epidemic dynamics and control in populations have raised increasing attentions using complex network models. Considering population contact networks as random networks, we investigate three topics focusing on different aspects of epidemic control: i) effects of two control approaches, quarantine and public health advisories are incorporated into an established Susceptible-Infected-Removed (SIR) dynamics model, and an optimization framework is built to find the optimal control strategy; ii) a generic system dynamics model is developed to account for vaccination during the SIR process, and a game-theoretical framework is built to investigate population voluntary vaccination behavior under vaccine-phobia during a disease outbreak; and iii) a minimum required vaccine problem to prevent an epidemic outbreak and an optimal vaccine allocation problem to mitigate local disease propagation are solved, with consideration of population heterogeneity. Results from these studies reveal interesting insights for decision-makers in both urban infrastructure planning and public health industries. All these studies highlight the dominating importance of those infrastructures/individuals that are better connected with the others in the disruption/disease propagation processes. Moreover, self-interested gaming behavior of a population are often found to have a negative impact on system-wide utilities.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Civil Engineering

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2019

Author dc:creator

• Lu, Liqun

Contributors dc:contributor

• Meidani, Hadi
• Ouyang, Yanfeng
• Cai, Ximing
• Smith, Rebecca Lee

• interdependent infrastructure systems
• epidemic control
• random networks

Statement dc:rights

• Copyright 2019 Liqun Lu

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/104880

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/104880