A self-learning simulated annealing algorithm for global optimizations of electromagnetic devices

Shiyou Yang, Jose Marcio Machado, Guangzheng Ni, Siu Lau Ho, Ping Zhou

Research output: Journal article publicationJournal articleAcademic researchpeer-review

21 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)1000-1003
Number of pages4
JournalIEEE Transactions on Magnetics
Issue number4 PART 1
Publication statusPublished - 1 Dec 2000


  • Domain elimination method
  • Global optimization
  • Self-learning ability
  • Simulated annealing algorithm

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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