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.
Authors
- dr hab. inż. Adrian Bekasiewicz link open in new tab ,
- prof. dr inż. Sławomir Kozieł link open in new tab ,
- Qingsha Cheng,
- John Bandler
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1137/brak
- Category
- Aktywność konferencyjna
- Type
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language
- angielski
- Publication year
- 2017
