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
fDate :
7/1/2000 12:00:00 AM
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;
Journal_Title :
Magnetics, IEEE Transactions on
