Simulation of a new hybrid particle swarm optimization algorithm

Ping Luo, Peihong Ni, Lihai Yao, Siu Lau Ho, Guangzheng Ni, Haixia Xia

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)


In this paper, a new hybrid Particle Swarm Optimization algorithm is introduced which makes use of the characteristics of Simulated Annealing method, and the crossover and mutation operations of Genetic Algorithms. Simulation results demonstrate that the proposed algorithm observes faster convergent rate for a certain class of optimal problems.
Original languageEnglish
Pages (from-to)705-710
Number of pages6
JournalInternational Journal of Applied Electromagnetics and Mechanics
Issue number1-4
Publication statusPublished - 4 Jun 2007


  • Crossover
  • Mutation
  • Optimization
  • Particle swarm optimization

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering
  • Electrical and Electronic Engineering


Dive into the research topics of 'Simulation of a new hybrid particle swarm optimization algorithm'. Together they form a unique fingerprint.

Cite this