A Comparison of Techniques for Optimal Infrastructure Restoration

Abstract

Major disruptions such as terror attacks, natural disasters and human failures can have large impacts on critical infrastructure. The rapid reconstitution of those infrastructure systems after a major disruption is crucial to minimize the impact of the disaster. This thesis compares two different modeling techniques to minimize the cost for reconstructing the infrastructure system. The first technique uses a mixed integer linear program to minimize the operation cost of a infrastructure system. The second technique is a graph-based approach in which the vertices of a meta graph represent different operating states for the infrastructure system, and edges between vertices represent possible transitions between states (e.g., the repair of one or more infrastructure components). In this context, optimal restoration of the infrastructure system corresponds to finding the best (e.g., minimum cost) path from an initial damaged state to a fully restored state. We consider two different ways of finding the shortest path in this meta graph, specifically Dijkstra s algorithm and the A-star algorithm. We compare these techniques in terms of quality of solution and required computation time.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 2014
Accession Number
ADA621458

Entities

People

  • Carsten Schulze

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies
  • Engineered Resilient Systems

DTIC Thesaurus Topics

  • Algorithms
  • Communication Systems
  • Computations
  • Computer Programming
  • Disasters
  • Emergencies
  • Emergency Response
  • Flow Network
  • Infrastructure
  • Linear Programming
  • Mathematical Programming
  • Natural Disasters
  • Operations Research
  • Python Programming Language
  • Systems Engineering
  • Systems Science
  • Transitions

Fields of Study

  • Computer science

Readers

  • Distributed Systems and Data Platform Development
  • Emergency Management and Homeland Security.
  • Operations Research