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Information Technology Journal
  Year: 2009 | Volume: 8 | Issue: 8 | Page No.: 1263-1268
DOI: 10.3923/itj.2009.1263.1268
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An Enhanced Particle Swarm Optimization Algorithm

Xue-yao Gao, Li-quan Sun and Da-song Sun

Particle Swarm Optimization (PSO) algorithm is often used for finding optimal solution, but it easily entraps into the local extremum in later evolution period. Based on improved chaos searching strategy, an enhanced particle swarm optimization algorithm is proposed in this study. When particles get into the local extremum, they are activated by chaos search strategy, where the chaos search area is controlled in the neighborhood of current optimal solution by reducing search area of variables. The new algorithm not only gets rid of the local extremum effectively but also enhances the precision of convergence significantly. Experiment results show that the proposed algorithm is better than standard PSO algorithm in both precision and stability.
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  •    Research on the Particle-Ant Colony Algorithm in Web Services Composition Problem
  •    Efficient Scheduling of Electricity Consumption for Smart Grid with Uncertainty in Renewable Supply
  •    A Layout Pattern Based Particle Swarm Optimization for Constrained Packing Problems
  •    Considering the Effect of Series Capacitor in Optimal Coordination of Directional Over-current Relays
How to cite this article:

Xue-yao Gao, Li-quan Sun and Da-song Sun, 2009. An Enhanced Particle Swarm Optimization Algorithm. Information Technology Journal, 8: 1263-1268.

DOI: 10.3923/itj.2009.1263.1268






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