Original scientific paper
https://doi.org/10.32985/ijeces.17.6.5
Evaluation of the performance of a novel Fitness Function improving Genetic Algorithm optimization of Micro Strip Patch Antennas
Manoj B
; Department of Instrumentation, Cochin University of Science and Technology (CUSAT), Kochi 682022, India
*
Stephen Rodrigues
; Department of Instrumentation, Cochin University of Science and Technology (CUSAT), Kochi 682022, India
* Corresponding author.
Abstract
Standard formulas may not produce the expected outcomes when designing Micro Strip Patch Antennas (MSPA). Finding the proper proportions can be accomplished through optimization. Over a quarter of a century has passed since the genetic algorithm (GA) was first applied to MSPA optimization. The fitness function (FF) is what drives the optimization algorithm. Here, multiple performance parameters of an MSPA are improved by optimizing its dimensions, the length Ly and width Wx, using a novel fitness function applying graded fitness and graded penalty. Three performance criteria are targeted by the antenna optimization: a 5 GHz operating frequency, a bandwidth BW exceeding 250 MHz spanning on each side of the center frequency, and a return loss S11 value of less than -20 dB. The performance of the proposed FF, when compared against the performance of the most popular five FFs, outperformed the other five FFs by achieving all three targeted performance criteria by returning an MSPA resonating at 5 GHz, with a return loss of -24.18 dB and a bandwidth of 270 MHz. HFSS and MATLAB were used for optimization along with RT Duroid as the material for the antenna.
Keywords
Micro Strip Patch Antenna; Genetic Algorithm; Optimization; Fitness function;
Hrčak ID:
347898
URI
Publication date:
15.6.2026.
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