HONG Tao, PENG Gang, LI Zhiping, LIANG Yi. A Novel Evolutionary Strategy for Particle Swarm Optimization[J]. Chinese Journal of Electronics, 2009, 18(4): 771-774.
Citation: HONG Tao, PENG Gang, LI Zhiping, LIANG Yi. A Novel Evolutionary Strategy for Particle Swarm Optimization[J]. Chinese Journal of Electronics, 2009, 18(4): 771-774.

A Novel Evolutionary Strategy for Particle Swarm Optimization

  • Received Date: 2009-01-01
  • Rev Recd Date: 2009-02-01
  • Publish Date: 2009-11-25
  • A novel evolutionary strategy for Particle swarm optimization (PSO) to enhance the convergencespeed and avoid the local optima is presented. The positive experience and negative lesson from the individualparticle's cognition and the swarm's social knowledge areused to accumulate the system's intelligence and guidethe swarm's evolution behaviors. The new generation ofswarms (named as Child Swarm) and the adjacent formerswarms (named as Parent Swarm) are mixed to select thesurvival of the fittest. The eliminated particles are replaced by the random particles from the outside surroundings. Darwinian evolution method contributes to the convergence and the durative interactions between the swarmsand the surroundings who contribute to the global search.This new method can converges faster, gives more robustand precise result and can prevent prematurity more effectively. The corresponding simulation results are presented.
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      沈阳化工大学材料科学与工程学院 沈阳 110142

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