Comparative analysis of metaheuristic algorithms (genetic algorithm, artificial bee colony, differential evolution) in the design of substrate integrated waveguide dual bandpass filter

Abstract

A well-optimized substrate integrated waveguide (SIW) filter can significantly enhance the performance of modern technologies, including wireless communication systems, radar, and sensors. The frequencies of 5 and 6 GHz play a crucial role in these applications. Metaheuristic algorithms such as genetic algorithm (GA), artificial bee colony (ABC), and differential evolution (DE) are effective for designing SIW filters specifically tailored to these needs. This paper evaluates the performance of evolutionary optimization techniques in the design of substrate integrated waveguide filters. The optimization focuses on achieving optimal impedance matching within the frequency range of 4 to 8 GHz. The attenuation constant serves as the cost function, guiding the optimization process to ensure reliable and accurate results from each algorithm. The filter parameters derived from the most efficient algorithm are verified using ANSYS HFSS, resulting in two bands with S11=-45 dB and S21=-0.2 dB in the first band, and S11=-28 dB and S21=-0.5 dB in the second band. Additionally, two transmission zeros with rejections of -23 and -12 dB are achieved at 6.4 and 7.08 GHz, respectively. These results highlight the practicality of SIW technologies in designing microwave circuits, particularly for internet of things (IoT) applications.