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Information Technology Journal
  Year: 2011 | Volume: 10 | Issue: 10 | Page No.: 1908-1916
DOI: 10.3923/itj.2011.1908.1916
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Multi-objective Optimization using Chaos Based PSO

Bingqun Ren and Weizhou Zhong

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.
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  •    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






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