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An Effective Robust Optimization Based on Genetic Algorithm
| Title: | An Effective Robust Optimization Based on Genetic Algorithm |
| Authors: | Maruyama, Takayuki Browse this author | | Igarashi, Hajime Browse this author →KAKEN DB |
| Keywords: | constraint condition | | electromagnetic application | | genetic algorithm (GA) | | robust optimization |
| Issue Date: | Jun-2008 |
| Publisher: | IEEE |
| Journal Title: | IEEE Transactions on Magnetics |
| Volume: | 44 |
| Issue: | 6 |
| Start Page: | 990 |
| End Page: | 993 |
| Publisher DOI: | 10.1109/TMAG.2007.916696 |
| Abstract: | Although probabilistic optimization methods based on genetic algorithm (GA) provides accurate results, its performance is sometimes considerably sensitive to parameter changes. Moreover, the constraints are violated due to such parameter changes. A robust GA which performs random perturbation during optimization processes has been applied to some mathematical problems to show that it works as fast as the usual GAs. An adequate elite reservation technique for the robust GA is presented and applied to the robust GA for electromagnetic problems. Moreover, this method is shown to find solutions which are kept feasible against parameter changes. |
| Rights: | © 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
| Type: | article |
| URI: | http://hdl.handle.net/2115/38721 |
| 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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