Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/890
| Title: | A self-learning simulated annealing algorithm for global optimizations of electromagnetic devices | Authors: | Yang, S Machado, JM Ni, G Ho, SL Zhou, P |
Issue Date: | Jul-2000 | Source: | IEEE transactions on magnetics, July 2000, v. 36, no. 4, p. 1004-1008 | Abstract: | A self-learning simulated annealing algorithm is developed by combining the characteristics of simulated annealing and domain elimination methods. The algorithm is validated by using a standard mathematical function and by optimizing the end region of a practical power transformer. The numerical results show that the CPU time required by the proposed method is about one third of that using conventional simulated annealing algorithm. | Keywords: | Domain elimination method Global optimization Self-learning ability Simulated annealing algorithm |
Publisher: | Institute of Electrical and Electronics Engineers | Journal: | IEEE transactions on magnetics | ISSN: | 0018-9464 | EISSN: | 1941-0069 | DOI: | 10.1109/20.877611 | Rights: | © 2000 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. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. |
| Appears in Collections: | Journal/Magazine Article |
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| self-learning-simulated_00.pdf | 69.5 kB | Adobe PDF | View/Open |
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