A Large Scale Integer Linear Program as a Decision Support Tool for Force Mix Selection

Abstract

In the post cold war environment, the rapid deployment of combat capability is critical. Deployment lift capability is limited, however, so the real-time selection of the optimal combat asset mix that balances capability provided and sustainment required has become paramount. In this model, the value of a force mix is determined by the sum of the individual weapon system "suitabilities" against their assigned missions. The value is constrained by the numerical limits on the items required to create and support the force mix, and the lift required to move these items. The research considered heuristic and complete enumeration methods against the problem structure to develop a decision support model that expedites the selection of the best overall force mix. War planners are provided a decision support tool that objectively compares alternative force mix packages and selects the optimal asset mix in a reasonable amount of time while explicitly considering logistics constraints. This demonstrates the feasibility of an approach that integrates intelligence, operations, and logistics issues into a single decision support and planning tool for force mix decisions.

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Document Details

Document Type
Technical Report
Publication Date
Mar 20, 2002
Accession Number
ADA399947

Entities

People

  • Craig A. Punches

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Contingency Operations (Military)
  • Control Systems
  • Deployment
  • Information Processing
  • Information Systems
  • Integer Programming
  • Linear Programming
  • Logistics
  • Mathematical Models
  • Mathematical Programming
  • Military Science
  • Operations Research
  • Test And Evaluation
  • War Colleges
  • Warfare
  • Weapon Control

Readers

  • Maritime Combat Support and Expeditionary Logistics.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.