2026-09-19T09:52:50Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1591022025-10-12T03:17:20Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Rhodes, Donna H.
Ballard, Zachary N.
System Design and Management Program.
2025-04-14T14:05:45Z
2025-04-14T14:05:45Z
2025-02
2025-03-07T19:31:48.043Z
https://hdl.handle.net/1721.1/159102
The United States Coast Guard is currently transforming its decision-making process for prioritizing shore infrastructure maintenance and repair projects. Current decision-making subjectivity appears to be generating inadequate project prioritizations. Stakes are high for an aging infrastructure portfolio in harsh coastal conditions, with increased national reliance on the Coast Guard in a fiscally constrained budgetary environment. Data availability, quality, and fidelity continue to increase, supporting the rationale for more robust and data-informed decision-making frameworks.
The research begins with examining Coastal and Shore Operations (CSO) funding history, along with a thorough description of the current Centralized Planned Obligation Prioritization (C-POP) process. The complex, sociotechnical nature of the problem is highlighted by identifying all involved stakeholders and categorizing them through the leading view of stakeholder theory and salience. A detailed review of the governing asset management literature is conducted, gradually narrowing from a broad, international, and asset-type neutral perspective to more tailored infrastructure cross-asset prioritization material. Requisite framework data substance, collection, and analyses are described, and recommendations for data processing improvements are made.
Two leading prioritization models are examined: the Importance and Urgency Quadrant Model and the Value Focused Multi-Criteria Decision Model. Their respective data visualizations are generated and analyzed. Using the multi-criteria analysis rooted in multi-attribute utility theory, four portfolios of measurably increasing value are constructed, compared with a baseline portfolio reflecting actual project selections in December 2023. These portfolio iterations include a linear programming solution to the Knapsack Problem of selecting projects that maximize overall portfolio utility within a budget limit while incorporating some of the more social and qualitative system properties.
A traceable, adaptable, defendable, and objective data-informed multi-criteria framework is proposed, which aims to facilitate the effectiveness of the overall Coast Guard shore infrastructure portfolio in the long term.
S.M.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright retained by author(s)
https://rightsstatements.org/page/InC-EDU/1.0/
Enhancing Coast Guard Infrastructure Management: A Multi-Criteria Framework for Prioritizing Maintenance Projects
Thesis
application/pdf
Master
Master of Science in Engineering and Management
Publication
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<Abstract>The United States Coast Guard is currently transforming its decision-making process for prioritizing shore infrastructure maintenance and repair projects. Current decision-making subjectivity appears to be generating inadequate project prioritizations. Stakes are high for an aging infrastructure portfolio in harsh coastal conditions, with increased national reliance on the Coast Guard in a fiscally constrained budgetary environment. Data availability, quality, and fidelity continue to increase, supporting the rationale for more robust and data-informed decision-making frameworks.
The research begins with examining Coastal and Shore Operations (CSO) funding history, along with a thorough description of the current Centralized Planned Obligation Prioritization (C-POP) process. The complex, sociotechnical nature of the problem is highlighted by identifying all involved stakeholders and categorizing them through the leading view of stakeholder theory and salience. A detailed review of the governing asset management literature is conducted, gradually narrowing from a broad, international, and asset-type neutral perspective to more tailored infrastructure cross-asset prioritization material. Requisite framework data substance, collection, and analyses are described, and recommendations for data processing improvements are made.
Two leading prioritization models are examined: the Importance and Urgency Quadrant Model and the Value Focused Multi-Criteria Decision Model. Their respective data visualizations are generated and analyzed. Using the multi-criteria analysis rooted in multi-attribute utility theory, four portfolios of measurably increasing value are constructed, compared with a baseline portfolio reflecting actual project selections in December 2023. These portfolio iterations include a linear programming solution to the Knapsack Problem of selecting projects that maximize overall portfolio utility within a budget limit while incorporating some of the more social and qualitative system properties.
A traceable, adaptable, defendable, and objective data-informed multi-criteria framework is proposed, which aims to facilitate the effectiveness of the overall Coast Guard shore infrastructure portfolio in the long term.</Abstract>
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