DocumentCode
1396755
Title
A self-learning simulated annealing algorithm for global optimizations of electromagnetic devices
Author
Yang, Shiyou ; Machado, Jose Marcio ; Ni, Guangzheng ; Ho, S.L. ; Zhou, Ping
Author_Institution
Dept. of Electr. Eng., Hong Kong Polytech., Kowloon, China
Volume
36
Issue
4
fYear
2000
fDate
7/1/2000 12:00:00 AM
Firstpage
1004
Lastpage
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
power engineering computing; power transformers; simulated annealing; unsupervised learning; CPU time; domain elimination methods; electromagnetic devices; end region; global optimizations; power transformer; self-learning simulated annealing algorithm; standard mathematical function; Computer science; Constraint optimization; Convergence; Electromagnetic devices; History; Optimization methods; Power transformers; Robustness; Simulated annealing; Stochastic processes;
fLanguage
English
Journal_Title
Magnetics, IEEE Transactions on
Publisher
ieee
ISSN
0018-9464
Type
jour
DOI
10.1109/20.877611
Filename
877611
Link To Document