Paper Title:
An Improved Particle Swarm Optimization Algorithm
  Abstract

An improved particle swarm optimization (IPSO) was proposed in this paper to solve the problem that the linearly decreasing inertia weight (LDIW) of particle swarm optimization algorithm cannot adapt to the complex and nonlinear optimization process. The strategy of nonlinear decreasing inertia weight based on the concave function was used in this algorithm. The aggregation degree factor of the swarm was introduced in this new algorithm. And in each iteration process, the weight is changed dynamically based on the current aggregation degree factor and the iteration times, which provides the algorithm with dynamic adaptability. The experiments on the three classical functions show that the convergence speed of IPSO is significantly superior to LDIWPSO, and the convergence accuracy is increased.

  Info
Periodical
Edited by
Wenya Tian and Linli Xu
Pages
454-458
DOI
10.4028/www.scientific.net/AMR.186.454
Citation
H. X. Cheng, J. Wang, "An Improved Particle Swarm Optimization Algorithm", Advanced Materials Research, Vol. 186, pp. 454-458, 2011
Online since
January 2011
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