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
Keywords: Domain elimination method
Global optimization
Self-learning ability
Simulated annealing algorithm
Issue Date: Jul-2000
Publisher: IEEE
Source: IEEE transactions on magnetics, July 2000, v. 36, no. 4, p. 1004-1008 How to cite?
Journal: IEEE transactions on magnetics 
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.
URI: http://hdl.handle.net/10397/890
ISSN: 0018-9464
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.
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