A parallel electromagnetic genetic-algorithm optimization (EGO) application for patch antenna design

In this paper, we describe an electromagnetic genetic algorithm (GA) optimization (EGO) application developed for the cluster supercomputing platform. A representative patch antenna design example for commercial wireless applications is detailed, which illustrates the versatility and applicability of the method. We show that EGO allows us to combine the accuracy of full-wave EM analysis with the robustness of GA optimization and the speed of a parallel computing algorithm. A representative patch antenna design case study is presented. We illustrate the use of EGO to design a dual-band antenna element for wireless communication (1.9 and 2.4 GHz) applications. The resulting antenna exhibits acceptable dual-band operation (i.e., better than -10 dB return loss with 5.3 and 7% operating bandwidths at 1.9 and 2.4 GHz) while maintaining a cross-pol maximum field level at least 11 dB below the co-pol maximum.