A Novel PSO Algorithm Model Based on Population Migration Strategy and its Application

نویسندگان

  • Shengli Song
  • Bing Lu
  • Li Kong
  • Jingjing Cheng
چکیده

According to the intelligent behavior of social population, the centroid of the individual best of particle swarm is firstly introduced in particle swarm optimization (PSO) model to enhance inter-particle cooperation and information sharing capabilities, then combining the mechanism of population migration algorithm (PMA), a novel PSO algorithm with adaptive space mutation (PMCPSO) is proposed to improve computing performance of PSO algorithm. Experiment results of Benchmark function and practical application in quality monitoring of laser welding process show the new algorithm has not only higher convergence precision and faster convergence speed, but also can avoid the premature convergence problem effectively.

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عنوان ژورنال:
  • JCP

دوره 6  شماره 

صفحات  -

تاریخ انتشار 2011