A COMPUTATIONAL FRAMEWORK FOR OPTIMIZATION-BASED INTERDEPENDENT INFRASTRUCTURE ANALYSIS AND VULNERABILITY
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Authors
Kuc, Matthias P.
Subjects
optimization
Python
Pyomo
framework
network flow
interdependence
dependence
Python
Pyomo
framework
network flow
interdependence
dependence
Advisors
Eisenberg, Daniel
Date of Issue
2020-12
Date
Publisher
Monterey, CA; Naval Postgraduate School
Language
Abstract
Civilian communities and military installations operate numerous critical infrastructure systems to deliver services like power, water, mobility, and communications to people and missions. The vulnerability of these systems can be measured by considering the robustness of each infrastructure network on its own or by considering the interdependencies between different networks. Diverse infrastructure network models are available to analyze system vulnerability, yet a standard architecture for linking pre-existing models for interdependent analysis does not exist. We develop a computational framework to generate combined models that link multiple network-flow optimization models together for interdependent analysis. We validate our methods and implementation in the Python programming language with well-studied interdependent energy networks. We further demonstrate the versatility of our methods by developing a new assessment of fictitious energy and transportation networks with models not originally created with interdependencies. Overall, this work develops a standard way to conduct interdependent infrastructure analysis with pre-built models and sets a foundation for future analysis of other interdependencies and systems.
Type
Thesis
Description
Series/Report No
Department
Operations Research (OR)
Organization
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Approved for public release. distribution is unlimited
Rights
Copyright is reserved by the copyright owner.