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2005
Springer

Hybrid Particle Swarm - Evolutionary Algorithm for Search and Optimization

9 years 5 months ago
Hybrid Particle Swarm - Evolutionary Algorithm for Search and Optimization
Particle Swarm Optimization (PSO) technique has proved its ability to deal with very complicated optimization and search problems. Several variants of the original algorithm have been proposed. This paper proposes a novel hybrid PSO - evolutionary algorithm for solving the well known geometrical place problems. Finding the geometrical place could be sometimes a hard task. In almost all situations the geometrical place consists more than one single point. The performance of the newly proposed PSO algorithm is compared with evolutionary algorithms. The main advantage of the PSO technique is its speed of convergence. Also, we propose a hybrid algorithm, combining PSO and evolutionary algorithms. The hybrid combination is able to detect the geometrical place very fast for which the evolutionary algorithms required more time and the conventional PSO approach even failed to find the real geometrical place.
Crina Grosan, Ajith Abraham, Sangyong Han, Alexand
Added 28 Jun 2010
Updated 28 Jun 2010
Type Conference
Year 2005
Where MICAI
Authors Crina Grosan, Ajith Abraham, Sangyong Han, Alexander F. Gelbukh
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