Intelligence Surveillance and Reconnaissance Asset Assignment for Optimal Mission Effectiveness

Abstract

This research develops mathematical programming techniques to solve an intelligence, surveillance, and reconnaissance sensor assignment problem for USSTRATCOM. The problem as specified is hypothesized to be difficult (i.e. np-hard). With the smallest test cases, the true optimal solution is found using simple optimization techniques, but, due to intractability, the optimal solutions for larger test cases are not found using these same techniques. Instead, heuristic techniques are applied to several test cases in order to determine the best, robust methodologies to find true or near optimal solutions. Specifically, simulated annealing (SA) is tested for convergence properties across several different parameter settings. This research also utilizes local search techniques with simple exchange neighborhoods of various sizes. Mission prioritization is also examined via a weighted sum scalarization technique.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2008
Accession Number
ADA485412

Entities

People

  • Ryan D. Kappedal

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Algorithms
  • Computational Fluid Dynamics
  • Department Of Defense
  • Equations
  • Genetic Algorithms
  • Governments
  • Heuristic Methods
  • Information Operations
  • Intelligence Surveillance And Reconnaissance
  • Mathematical Programming
  • Multiobjective Optimization
  • Operations Research
  • Optimization
  • Reliability
  • Surveillance
  • United States Government

Fields of Study

  • Computer science

Readers

  • Aerospace Engineering.
  • Operations Research