Paper Title:
A Multi-Swarm Cooperative Perturbed Particle Swarm Optimization
  Abstract

Combined with a variety of ideas a Multi-swarm cooperative Perturbed Particle Swarm Optimization algorithm (MpPSO) is presented to improve the performance and to reduce the premature convergence of PSO. This algorithm includes the idea of multiple swarms to improve the evolution efficiency by information sharing between populations to avoid falling into local optimum caused by single population. It also includes the idea of perturbing the swarms beside the global best solution, which can escape from local optimum. Experiments show that the proposed algorithm MpPSO has better performance, better convergence and stability when comparing with the traditional and the recently improved particle swarm optimization.

  Info
Periodical
Advanced Materials Research (Volumes 225-226)
Edited by
Helen Zhang, Gang Shen and David Jin
Pages
619-622
DOI
10.4028/www.scientific.net/AMR.225-226.619
Citation
X. J. Yang, Y. L. Zhao, Y. C. Chen, X. C. Zhao, "A Multi-Swarm Cooperative Perturbed Particle Swarm Optimization", Advanced Materials Research, Vols. 225-226, pp. 619-622, 2011
Online since
April 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Xiao Hua Wang, Yong Mei Zhang
Abstract:On the premise of ensuring safety and reliability in electricity market environment, the goal of State Grid Corporation is that purchase AGC...
274
Authors: Jun Zhang, Kan Yu Zhang
Chapter 19: Modeling, Analysis, and Simulation of Manufacturing Processes II
Abstract:Good dynamic performance of a system have great significance in the traditional sense, furthermore,it is more important at the point of...
4768
Authors: Da Wang, Hong Yu Bian
Chapter 1: Mechatronics
Abstract:In order to further improve the accuracy of the sonar image registration, a novel hybrid algorithm was proposed. It proposed the normalized...
1811
Authors: Wei Hua Fang
Chapter 6: Applied Mechanics
Abstract:In order to obtain geotechnical engineering material mechanical parameters correctly by using back analysis and overcome shortcoming of...
1647
Authors: Bei Zhan Wang, Xiang Deng, Wei Chuan Ye, Hai Fang Wei
Chapter 13: Mechanical Control and Information Processing Technology
Abstract:The particle swarm optimization (PSO) algorithm is a new type global searching method, which mostly focus on the continuous variables and...
1787