Efficient Microstrip Bandpass Filter Design by a Surrogate-Model-Assisted Improved Decomposition-Based Multi-Objective Differential Evolution Algorithm

A one-dimensional convolutional autoencoder (1D-CAE) assisted improved decomposition-based multiobjective differential evolution (IMODEA/D) algorithm is proposed for electromagnetic (EM) optimization in microstrip bandpass filter design. The 1D-CAE is employed as a surrogate model to accelerate the...

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Vydané v:International Conference on Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications (Online) Ročník 1; s. 1 - 3
Hlavní autori: Wang, Zeyu, Zhang, Lu, Li, Kun-Lai, Zhang, Yongliang
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 29.07.2025
Predmet:
Autoencoders
Band-pass filters
Convergence
Electromagnetic (EM) optimization
Electromagnetics
microstrip bandpass filter design
Microstrip filters
multi-objective optimization algorithm
Multiphysics
Numerical models
Optimization
surrogate model
ISSN:2575-4769
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Shrnutí:A one-dimensional convolutional autoencoder (1D-CAE) assisted improved decomposition-based multiobjective differential evolution (IMODEA/D) algorithm is proposed for electromagnetic (EM) optimization in microstrip bandpass filter design. The 1D-CAE is employed as a surrogate model to accelerate the design process. In addition, the convergence of the MOEA/D algorithm is improved by adding extreme value optimization and modifying the individual selection, mutation probability, boundary optimization strategy and replacing the crossover operation in the differential evolution (DE) algorithm with the simulated binary crossover (SBX). The efficiency of the proposed method is verified by a planar microstrip bandpass filter.
ISSN:2575-4769
DOI:10.1109/NEMO62710.2025.11215258