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Proceedings Paper

Optimum design of antennas using metamaterials with the efficient global optimization (EGO) algorithm
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Paper Abstract

EGO is an evolutionary, data-adaptive algorithm which can be useful for optimization problems with expensive cost functions. Many antenna design problems qualify since complex computational electromagnetics (CEM) simulations can take significant resources. This makes evolutionary algorithms such as genetic algorithms (GA) or particle swarm optimization (PSO) problematic since iterations of large populations are required. In this paper we discuss multiparameter optimization of a wideband, single-element antenna over a metamaterial ground plane and the interfacing of EGO (optimization) with a full-wave CEM simulation (cost function evaluation).

Paper Details

Date Published: 15 April 2010
PDF: 10 pages
Proc. SPIE 7704, Evolutionary and Bio-Inspired Computation: Theory and Applications IV, 770408 (15 April 2010); doi: 10.1117/12.851794
Show Author Affiliations
Hugh L. Southall, Air Force Research Lab. (United States)
Teresa H. O'Donnell, Air Force Research Lab. (United States)
John S. Derov, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 7704:
Evolutionary and Bio-Inspired Computation: Theory and Applications IV
Teresa H. O'Donnell; Misty Blowers; Kevin L. Priddy, Editor(s)

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