A robust metaheuristic combining clonal colony optimization and population-based incremental learning methods

Siu Lau Ho, Shiyou Yang, Yanan Bai, Jin Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

6 Citations (Scopus)


To provide a fast robust optimizer for numerical solutions of inverse problems, a metaheuristic combining a clonal colony optimization methodology and a population based incremental learning method is proposed. In the proposed algorithm, a real-valued probability vector is introduced for the extension of each colony; a tournament-based mechanism is employed in a colony to destruct/discard plants to evolve the colony toward a promising space; and a new reallocation operator is designed. The numerical results on two case studies are reported to positively showcase the feasibilities and merits of the proposed metaheuristic.
Original languageEnglish
Article number6749035
JournalIEEE Transactions on Magnetics
Issue number2
Publication statusPublished - 1 Feb 2014


  • Evolutionary computation
  • inverse problem
  • robustness
  • uncertainty

ASJC Scopus subject areas

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

Cite this