An Adaptive Particle Swarm Optimization Algorithm Based on Cloud Model

Abstract:

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In this paper, an adaptive particle swarm optimization algorithm based on cloud model (C-APSO) is proposed. In the suggested method, the velocities of the all particles are adjusted based on the strategy that a particle whose fitness value is nearer to the optimal particle will fly with smaller velocity. Considering the properties of randomness and stable tendency of a normal cloud model, a Y-conditional normal cloud generator is used to gain the inertial factors of the particles. The simulations of function optimization show that the proposed method has advantage of global convergence property and can effectively alleviate the problem of premature convergence.

Info:

Periodical:

Advanced Materials Research (Volumes 129-131)

Edited by:

Xie Yi and Li Mi

Pages:

612-616

DOI:

10.4028/www.scientific.net/AMR.129-131.612

Citation:

J. R. Zhu "An Adaptive Particle Swarm Optimization Algorithm Based on Cloud Model", Advanced Materials Research, Vols. 129-131, pp. 612-616, 2010

Online since:

August 2010

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Price:

$35.00

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