Constrained Surrogates and Dimensionality Reduction for Low-Cost Multi-Objective Optimization of Compact Microwave Components

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Abstract

This paper addresses the problem of expedited surrogate-assisted multi-objective optimization of compact microwave passives. Our methodology adopts the concept of constrained modeling, enhanced by a reduction of the parameter space dimensionality. The latter is realized through the spectral analysis of the supplementary reference design set used to estimate the geometry of the Pareto front. As demonstrated using a 15-parameter impedance transformer, the combination of these mechanisms permits identification of the Pareto set at the cost of just a few hundred of EM circuit simulations. Benchmarking reveals considerable efficiency improvements achieved over the state-of-the-art surrogate-based MO algorithms.

Original languageEnglish
Title of host publication2021 IEEE MTT-S International Microwave Symposium, IMS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages237-240
Number of pages4
ISBN (Electronic)9781665403078
DOIs
Publication statusPublished - 7 Jun 2021
Event2021 IEEE MTT-S International Microwave Symposium, IMS 2021 - Virtual, Atlanta, United States
Duration: 7 Jun 202125 Jun 2021

Publication series

NameIEEE MTT-S International Microwave Symposium Digest
Volume2021-June

Conference

Conference2021 IEEE MTT-S International Microwave Symposium, IMS 2021
Country/TerritoryUnited States
CityVirtual, Atlanta
Period7/06/2125/06/21

Bibliographical note

Funding Information: ACKNOWLEDGMENT The authors would like to thank Dassault Systemes, France, for making CST Microwave Studio available. This work was supported in part the Icelandic Centre for Research (RANNIS) Grant 217771051 and by National Science Centre of Poland Grant 2018/31/B/ST7/02369, and by Bandler Corporation. Publisher Copyright: © 2021 IEEE.

Other keywords

  • compact components
  • dimensionality reduction
  • microwave design
  • multi-objective optimization
  • surrogate modeling

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