An improved cooperative particle swarm optimization and its application |
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Authors: | Debao Chen Chunxia Zhao Haofeng Zhang |
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Affiliation: | (1) The School of Physics and Electronic Information, Huai Bei Normal University, 235000 Huaibei, China;(2) Computer Institute of NanJing University of Science and Technology, 210094 Nanjing, China |
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Abstract: | A powerful cooperative evolutionary particle swarm optimization (PSO) algorithm based on two swarms with different behaviors
to improve the global performance of PSO is proposed. In this method, one swarm tracks the best position and the other leaves
the worst position of them; the best and the worst solutions of the two swarms are exchanged in the common blackboard and
the information can be flowed mutually between them. The diversity is maintained if the two swarms are regarded as a whole.
To show the effectiveness of the given algorithm, five benchmark functions and two forward ANNs with three layers are performed;
the results of the proposed algorithms are compared with standard PSO, MCPSO and NPSO. |
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Keywords: | |
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