Subscribe Now Subscribe Today
Science Alert
 
Blue
   
Curve Top
Information Technology Journal
  Year: 2011 | Volume: 10 | Issue: 10 | Page No.: 1908-1916
DOI: 10.3923/itj.2011.1908.1916
 
Facebook Twitter Digg Reddit Linkedin StumbleUpon E-mail

Multi-objective Optimization using Chaos Based PSO

Bingqun Ren and Weizhou Zhong

Abstract:
As a novel optimization method, chaos has gained lots of attentions and applications in the past few years. Chaos movement can go through all states unrepeated according to the rule of itself in some area. It was introduced into the optimization strategy to accelerate the optimum seeking operation in this study. A chaos based particle swarm optimization strategy was developed to solve multi-objective optimization problems. The proposed approach is validated using several benchmark test functions and metrics on evolutionary multi-objective optimization. Results demonstrate the effectiveness and efficiency of the proposed strategy and that can be considered a viable alternative to solve multi-objective optimization problems.
PDF Fulltext XML References Citation Report Citation
 RELATED ARTICLES:
  •    Convergence and Spectral Radius Analysis and Parameter Selection for the Particle Swarm Optimization Algorithm Based on the Stochastic Process
  •    Multicriteria Decision Mechanism CNSGA-AHP for the Automatic Test Task Scheduling Problem
  •    Design of Robust PID Controller Using Hybrid Algorithm for Reduced Order Interval System
  •    The Development of a Particle Swarm Based Optimization Strategy for Pairwise Testing
  •    Dynamic Optimal Power Flow in FSWGs Integrated Power System
  •    An Efficient Process Mining Method Based on Discrete Particle Swarm Optimization
  •    Research on Learning Bayesian Networks by Particle Swarm Optimization
How to cite this article:

Bingqun Ren and Weizhou Zhong, 2011. Multi-objective Optimization using Chaos Based PSO. Information Technology Journal, 10: 1908-1916.

DOI: 10.3923/itj.2011.1908.1916

URL: https://scialert.net/abstract/?doi=itj.2011.1908.1916

COMMENT ON THIS PAPER
 
 
 

 

 
 
 
 
 
 
 
 
 

 
 
 
 
 

Curve Bottom