A Post-Disaster Construction Portfolio Optimization Framework for Tyndall AFB Rebuild Post Hurricane Michael

Abstract

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 spanning individual facilities to enterprise or municipal campuses. For multi-facility portfolios, post-disaster reconstruction must be properly prioritized to ensure facilities and infrastructure are restored, and any expansion or new construction initiatives are completed, in order of precedence, as defined by decision-maker and community needs. Many post-disaster optimization and decision frameworks consider a portfolio project with one main stakeholder. 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.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2022
Accession Number
AD1174064

Entities

People

  • Andre J. May

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Algorithms
  • Applied Mathematics
  • Civil Engineering
  • Construction
  • Engineering
  • Engineers
  • Floods
  • Flow Network
  • Genetic Algorithms
  • Governments
  • Hurricanes
  • Infrastructure
  • Integer Programming
  • Linear Programming
  • Mathematical Programming
  • National Security
  • Natural Disasters
  • Optimization
  • Particle Swarm Optimization
  • Systems Engineering
  • United States

Readers

  • Economics
  • Emergency Management and Homeland Security.
  • Operations Research