Improved Quantum-Behaved Particle Swarm Algorithm Based on Levy Flight

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 t...

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Bibliographic Details
Published in:Mathematical problems in engineering 2020, Vol.2020 (2020), p.1-10
Main Authors: Ge, Ming, Zheng, Xiaoqing, Zhou, Xinwei, Zheng, Song
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Computer simulation
Convergence
Directivity
Foraging behavior
Optimization algorithms
Particle swarm optimization
Search process
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Summary: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.
ISSN:1024-123X
1563-5147
DOI:10.1155/2020/3230643