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A Comprehensive Optimal Design of Inductors Using Monte Carlo Tree Search
| Title: | A Comprehensive Optimal Design of Inductors Using Monte Carlo Tree Search |
| Authors: | Yin, Shuli Browse this author | | Sato, Hayaho Browse this author | | Igarashi, Hajime Browse this author →KAKEN DB |
| Keywords: | inductors | | Monte Carlo tree search (MCTS) | | non-linear electromagnetic problems | | optimal strategy |
| Issue Date: | Mar-2024 |
| Publisher: | IEEE (Institute of Electrical and Electronics Engineers) |
| Journal Title: | IEEE transactions on magnetics |
| Volume: | 60 |
| Issue: | 3 |
| Start Page: | 8400504 |
| Publisher DOI: | 10.1109/TMAG.2023.3308214 |
| Abstract: | This article presents a strategy of optimizing inductors with non-linear properties, using Monte Carlo tree search (MCTS). Compared with the existing optimization tools, the proposed method can simultaneously optimize global configuration, such as material, number of turns and winding arrangement, and local geometry. It indicates that the strategy statistically provides a best solution from global and local aspects after iterations with different lengths of chromosomes, which is challenging in conventional optimization techniques. The covariance matrix adaptation evolution strategy (CMA-ES) is used to solve the parametric optimization. For validation, the optimizations on 2-D inductors are performed. The proposed method is very suitable for the optimization of devices with possibly different global configurations. The most notable originality of this work is in the proposal of an inherited search for design targets with different emphases, suggesting that using an inherited search from the previous search history can make it easier to find the optimal solution. |
| Rights: | © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Type: | article (author version) |
| URI: | http://hdl.handle.net/2115/92444 |
| Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 五十嵐 一
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