A new implementation of population based incremental learning method for optimizations in electromagnetics

S. Y. Yang, Siu Lau Ho, G. Z. Ni, José Márcio Machado, K. F. Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

27 Citations (Scopus)


To enhance the global search ability of population based incremental learning (PBIL) methods, it is proposed that multiple probability vectors are to be included on available PBIL algorithms. The strategy for updating those probability vectors and the negative learning and mutation operators are thus re-defined correspondingly. Moreover, to strike the best tradeoff between exploration and exploitation searches, an adaptive updating strategy for the learning rate is designed. Numerical examples are reported to demonstrate the pros and cons of the newly implemented algorithm.
Original languageEnglish
Pages (from-to)1601-1604
Number of pages4
JournalIEEE Transactions on Magnetics
Issue number4
Publication statusPublished - 1 Apr 2007


  • Genetic algorithm (GA)
  • Global optimization
  • Inverse problem
  • Population based incremental learning (PBIL) method

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Physics and Astronomy (miscellaneous)

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