Affiliation:
1. Hangzhou Dianzi University College of Automation, Hangzhou, China
Abstract
To improve convergence speed and search accuracy, this paper proposes an improved quantum-behaved particle swarm optimization algorithm based on Levy flight. The improved algorithm reduces the probability of a local optimal solution through Levy flight and enhances the accuracy of the later search through a postsearch strategy. During the search process, the probability of quantum behavior is retained and the directivity of the particles is strengthened. According to the simulation comparison results, the improved quantum-behaved particle swarm algorithm exhibits faster convergence speed and higher accuracy.
Funder
National Natural Science Foundation of China
Subject
General Engineering,General Mathematics
Cited by
1 articles.
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