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

Hugh L. Southall; Teresa H. O'Donnell; John S. Derov

doi:10.1117/12.851794

15 April 2010 Optimum design of antennas using metamaterials with the efficient global optimization (EGO) algorithm

Hugh L. Southall, Teresa H. O'Donnell, John S. Derov

Proceedings Volume 7704, Evolutionary and Bio-Inspired Computation: Theory and Applications IV; 770408 (2010) https://doi.org/10.1117/12.851794
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

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).

Citation Download Citation

Hugh L. Southall, Teresa H. O'Donnell, and John S. Derov "Optimum design of antennas using metamaterials with the efficient global optimization (EGO) algorithm", Proc. SPIE 7704, Evolutionary and Bio-Inspired Computation: Theory and Applications IV, 770408 (15 April 2010); https://doi.org/10.1117/12.851794

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