Date of Award

3-2000

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Operational Sciences

First Advisor

Raymond R. Hill, PhD

Abstract

The United States Air Force is increasingly facing more diverse threat situations while existing force structure levels are being reduced and proposed compositions are being severely scrutinized for relevance, affordability, and effectiveness. Military planners are struggling with the question of how to generate a single force structure that can adequately respond to a multitude of threat scenarios in an uncertain future while at the same time being tasked to prove just how effective their choice will be. In the past, modeling has been effective in showing how a force can respond to a single threat scenario but a new modeling technique needs to be developed for constructing a robust force capable of success across a gambit of scenarios. This thesis proposes a meta-heuristic approach to solving the planner's multi-scenario optimization problem. The approach makes use of an existing single scenario optimizer, the Combat Forces Assessment Model (CFAM), a public domain genetic algorithm, GENESIS, and a Visual Basic controller module to link them together. The approach is demonstrated by finding a robust AEF strike force tasked against three notional AEF threat scenarios.

AFIT Designator

AFIT-GOR-ENS-00M-04

DTIC Accession Number

ADA378296

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