A quantum-based particle swarm optimization algorithm applied to inverse problems

Siu Lau Ho, Shiyou Yang, Guangzheng Ni, Jin Huang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

30 Citations (Scopus)


To balance exploration and exploitation searches in order to prevent premature convergences in Particle Swarm Optimization (PSO) algorithms, an improved Quantum-based PSO (QPSO) algorithm is proposed with an ultimate goal of preserving the simplicities of available QPSOs. The improvements include the design of diversification and intensification phases, searching mechanisms and a strategy to shift away from the worst solutions. The proposed QPSO are compared to available optimizers on two case studies to showcase its merits.
Original languageEnglish
Article number6514656
Pages (from-to)2069-2072
Number of pages4
JournalIEEE Transactions on Magnetics
Issue number5
Publication statusPublished - 22 May 2013


  • Evolutionary algorithm
  • inverse problem
  • optimal design
  • particle swarm optimization

ASJC Scopus subject areas

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


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