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UKSim 2009: 11th International Conference on Computer Modelling and Simulation
A Score Based Method for Controlling the Convergence Behavior of Particle Swarm Optimization
March 25-March 27
ISBN: 978-0-7695-3593-7
In recent years, Particle Swarm Optimization (PSO)has been used in data mining, feature extraction andother optimization based applications. Time to time, anumber of researchers have suggested modifications tothe basic PSO. Although this optimization techniquefinds good solutions much faster than the traditionaland evolutionary algorithms, they suffer from a majordrawback of premature convergence. In addition, ithas been found experimentally that the quality of thesolutions does not improve as the number of iterationsis increased. In this paper we discuss the reasonbehind the premature convergence. We present a newmethod based on performance-scoring for improvingthe algorithm The scoring based model is applied tothe basic and some of the modified versions of PSOmodels.
Index Terms:
Particle Swarm Optimization ; Social network; Convergence; Constriction factor; Local best; Global best; Scoring factor
Citation:
Satish Chandra, Rajesh Bhat, D.S. Chauhan, "A Score Based Method for Controlling the Convergence Behavior of Particle Swarm Optimization," uksim, pp.19-24, UKSim 2009: 11th International Conference on Computer Modelling and Simulation, 2009
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