Optimizing Force Deployment and Force Structure for the Rapid Deployment Force

Abstract

This paper describes a goal programming approach to modeling the rapid deployment of combat units which offers decisive advantages over any current methodology. It accounts for both intertheater and intratheater airlift, and can be used to optimally plan movement schedules for predetermined forces or optimally choose and move a force from a list of available units and airlift resources to meet specified goals. Both methods are demonstrated, showing that the goal programming model minimizes wasted resources and accomplishes desired goal both faster and more exactly than the current interservice operating system. The model developed for demonstration uses 212 variables and 136 separate equations. In addition, a flexible response surface methodology is used to generate a full parametric sensitivity analysis, resulting in the reduction of a fully computerized and intricate large scale programming model to an equation programmable on a hand-held calculator, with minimal error. A demonstration is presented comparing relative advantages of C-5 and C-17 aircraft procurement, in a proposed addition of 50 aircraft to the current airlift fleet, with simultaneously varying airport capacities and deployment distances.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1984
Accession Number
ADA141148

Entities

People

  • J. C. Cooke

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Cyber
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Airframes
  • Combat Areas
  • Computer Programming
  • Employment
  • Fighter Aircraft
  • Goal Programming
  • Integer Programming
  • Linear Programming
  • Mathematical Models
  • Operating Systems
  • Operations Research
  • Rapid Deployment
  • Transport Aircraft
  • War Colleges
  • Warfare

Readers

  • Aerospace logistics and air mobility.
  • Computational Modeling and Simulation
  • Operations Research