{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/104880"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/104880","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Analysis and operations in complex networked systems: From urban infrastructure to epidemics","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Lu, Liqun"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Civil Engineering","degree_department":null,"school":null,"contributors":["Meidani, Hadi","Ouyang, Yanfeng","Cai, Ximing","Smith, Rebecca Lee"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-08-23T19:55:48Z","date_published":"2019-08-23T19:55:48Z","updated_at":"2026-07-22T22:24:42Z","subjects":["interdependent infrastructure systems","epidemic control","random networks"],"languages":["en"],"rights":["Copyright 2019 Liqun Lu"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/104880","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Meidani, Hadi","Ouyang, Yanfeng","Cai, Ximing","Smith, Rebecca Lee"]},{"key":"dc:creator","label":"Author","values":["Lu, Liqun"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-08-23T19:55:48Z","2019-04-19","2019-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Civil Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["interdependent infrastructure systems","epidemic control","random networks"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Liqun Lu"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/104880"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2019-08-22 without embargo terms","The student, Liqun Lu, accepted the attached license on 2019-04-19 at 09:04.","The student, Liqun Lu, submitted this Dissertation for approval on 2019-04-19 at 09:17.","This Dissertation was approved for publication on 2019-04-19 at 11:06.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13775 on 2019-08-22 at 14:45:02","Made available in DSpace on 2019-08-23T19:55:48Z (GMT). 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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.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2019-08-22 without embargo terms","The student, Liqun Lu, accepted the attached license on 2019-04-19 at 09:04.","The student, Liqun Lu, submitted this Dissertation for approval on 2019-04-19 at 09:17.","This Dissertation was approved for publication on 2019-04-19 at 11:06.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13775 on 2019-08-22 at 14:45:02","Made available in DSpace on 2019-08-23T19:55:48Z (GMT). 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