Paper Title:
A Chaos Particle Swarm Optimization Based on Adaptive Inertia Weight
  Abstract

In this paper, the chaotic optimization algorithm is embedded in traditional PSO algorithm using randomness and ergodicity of the chaotic characteristic, and random numbers and a inertia weight factor in PSO algorithm is substituted respectively by chaotic variables and an adaptive inertia weight function, so the ACEPSO algorithm is proposed in order to overcome the drawbacks of CPSO algorithm that easily falls into local optimum. With the simulation experiments, the effectiveness of ACEPSO algorithm is verified by optimization tests with the complex multi-dimensional function. The simulation results verify that the ACEPSO algorithm is robust, high precision, and strong global convergence, and is a kind of practical and feasible optimization algorithm.

  Info
Periodical
Key Engineering Materials (Volumes 474-476)
Edited by
Garry Zhu
Pages
1458-1463
DOI
10.4028/www.scientific.net/KEM.474-476.1458
Citation
Z. Jie, "A Chaos Particle Swarm Optimization Based on Adaptive Inertia Weight", Key Engineering Materials, Vols. 474-476, pp. 1458-1463, 2011
Online since
April 2011
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Price
$32.00
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