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2009 WRI World Congress on Computer Science and Information Engineering
Improved PSO Algorithm with Adaptive Inertia Weight and Mutation
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
In order to avoid premature convergence to local minimum, an improved particle swarm optimization (PSO) algorithm is proposed in this paper. The proposed approach adaptively adjusts its inertia weight according to the change of population fitness, and executes its mutation operation in accordance with its population density. The algorithm's performance is tested through three typical test function experiments. The test results and analysis show that it obviously enhances the performance and improves the population density.
Citation:
Mo Lin, Zheng Hua, "Improved PSO Algorithm with Adaptive Inertia Weight and Mutation," csie, vol. 4, pp.622-625, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
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