Date of Award

3-2005

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Gary B. Lamont, PhD

Abstract

The United States Air Force has put an increased emphasis on the timely delivery of precision weapons. Part of this effort has been to us multiple bay aircraft such the B-1B Lancer and B-52 Stratofortress to provide Close Air Support and responsive strikes using 1760 weapons. In order to provide greater flexibility, the aircraft carry heterogeneous payloads which can require deconfliction in order to drop multiple different types of weapons. Current methods of deconfliction and weapon selection are highly crew dependent and work intensive. This research effort investigates the optimization of an algorithm for weapon release which allows the aircraft to perform deconfliction automatically. This reduces crew load and response time in order to deal with time-sensitive targets. The overall problem maps to the Job-Shop Scheduling problem. Optimization of the algorithm is done through the General Multiobjective Parallel Genetic Algorithm (GENMOP). We examine the results from pedagogical experiments and real-world test scenarios in the light of improving decision making. The results are encouraging in that the program proves capable of finding acceptable release schedules, however the solution space is such that applying the program to real world situations is unnecessary. We present visualizations of the schedules which demonstrate these conclusions.

AFIT Designator

AFIT-GCE-ENG-05-04

DTIC Accession Number

ADA435191

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