Thesis (M.S. in Telecommunications Systems Management)--Naval Postgraduate School, September 1990. / Thesis Advisor(s): Tulloch, Allan W. Second Reader: Boger, Dan C. "September 1990." Description based on title screen as viewed on December 29, 2009. DTIC Identifier(s): Divestiture. Author(s) subject terms: Telephone, telecommunications, phone. Includes bibliographical references (p. 116-120). Also available in print.

Thesis (M.S. in Joint Campaign Planning and Strategy)--Joint Forces Staff College, Joint Advanced Warfighting School, 2007. / Title from title screen; viewed on July 9, 2007. "17 May 07." Electronic version of original print document. Includes bibliographical references (p. 78-83).

Thesis (MEngineering)--University of South Australia, 2001

Thesis--School of Advanced Airpower Studies, 1993. / Shipping list no.: 1998-0921-M. "September 1994." Includes bibliographical references. Also available via Internet from the Air University Press web site. Address as of 10/28/03: http://aupress.au.af.mil/SAAS%5FTheses/Hust/hust.pdf; current access is available via PURL.

Particle Swam Optimization (PSO) is especially useful for rapid optimization of problems involving multiple objectives and constraints in dynamic environments. It regularly and substantially outperforms other algorithms in benchmark tests. This paper describes research leading to the application of PSO to the autonomous asset management problem in electronic warfare. The PSO speed provides fast optimization of frequency allocations for receivers and jammers in highly complex and dynamic environments. The key contribution is the simultaneous optimization of the frequency allocations, signal priority, signal strength, and the spatial locations of the assets. The fitness function takes into account the assets' locations in 2 dimensions, maximizing their spatial distribution while maintaining allocations based on signal priority and power. The fast speed of the optimization enables rapid responses to changing conditions in these complex signal environments, which can have real-time battlefield impact. Results optimizing receiver frequencies and locations in 2 dimensions have been successful. Current run-times are between 450ms (3 receivers, 30 transmitters) and 1100ms (7 receivers, 50 transmitters) on a single-threaded x86 based PC. Run-times can be substantially decreased by an order of magnitude when smaller swarm populations and smart swarm termination methods are used, however a trade off exists between run-time and repeatability of solutions. The results of the research on the PSO parameters and fitness function for this problem are demonstrated.