Search
Abstract
In the paper, the problem of fast multi-objective optimization of compact impedance matching transformers is addressed by utilizing a novel Pareto ranking bisection algorithm. It approximates the Pareto front by dividing line segments connecting the designs found in the previous iterations, and refining the obtained candidate solutions by means of poll-type search involving Pareto ranking. The final Pareto set is obtained using surrogate-based optimization techniques. Our approach is validated using a compact impedance matching transformer and compared to state-of-the-art surrogate-assisted techniques.
Citations
-
0
CrossRef
-
0
Web of Science
-
0
Scopus
Authors (4)
-
Qingsha Cheng
- Southern University of Science and Technology
-
John Bandler
- McMaster University
Cite as
Full text
full text is not available in portal
Keywords
Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- International Applied Computational Electromagnetics Society Symposium strony 1 - 4
- Language:
- English
- Publication year:
- 2017
- Bibliographic description:
- Bekasiewicz A., Kozieł S., Cheng Q., Bandler J.: EM-Driven Multi-Objective Design of Impedance Transformers By Pareto Ranking Bisection Algorithm// International Applied Computational Electromagnetics Society Symposium/ : , 2017, s.1-4
- DOI:
- Digital Object Identifier (open in new tab) 10.1137/brak
- Verified by:
- Gdańsk University of Technology
seen 100 times
Recommended for you
Multi-objective design of miniaturized impedance transformers by domain segmentation
- S. Kozieł,
- A. Bekasiewicz,
- Q. Cheng
- + 1 authors
2017