Date of Award
Master of Science
Department of Systems Engineering and Management
Justin D. Delorit, PhD
Natural disasters such as hurricanes, earthquakes, tsunamis, and extreme flooding cause severe social and economic disruptions. Restoration of social and revenue-generating services often requires extensive reconstruction, from the facility to the campus scale. For multi-facility portfolios, decision-makers must prioritize post-disaster reconstruction activities appropriately to ensure facilities and infrastructure are restored. In addition, any expansion or new construction initiatives are ideally completed in order of decision-maker and community preference. Most post-disaster optimization and decision framework research consider a single stakeholder as guiding decisions related to a project portfolio. However, these portfolio prioritization frameworks ignore the effect of multiple stakeholders and competing priorities, as well as project complexity, as it relates to project risk. This research incorporates stakeholder priority and risk mitigation objectives in an optimization framework that targets the efficient prioritization or ordering of projects in a complex portfolio. Here a mixed-integer linear programming (MILP) optimization framework is proposed that prioritizes a project portfolio through complexity index-based risk mitigation and multi-stakeholder priority objectives, subject to an iteratively relaxed budget constraint. The relaxation of the budget constraint reveals the order in which projects should be done and the degree to which the solution—number and sequence of projects—are stable under budget changes. The results reveal that low cost, high mission impact projects are preferred over high cost, low mission impact projects. While this result is expected, the model and framework can facilitate recovery and new-mission bed down in the face of future natural disasters, contingency operations, or mission expansion, where competing priorities are many and complexity is high. While the mission priorities of the Air Force are used to create the optimized project sequences, the preferences can be transformed to meet a variety of stakeholder needs in the public sector, higher education, or healthcare sector.
DTIC Accession Number
May, Andre J., "A Post-disaster Construction Portfolio Optimization Framework for Tyndall AFB Rebuild Post Hurricane Michael" (2022). Theses and Dissertations. 5412.