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A New Quantum-Behaved Particle Swarm Optimization with a Chaotic Operator

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Intelligent Computing, Networked Control, and Their Engineering Applications (ICSEE 2017, LSMS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 762))

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Abstract

Particle Swarm Optimization has attracted many researcher to do further improvement on many real world problems. The quantum-behaved PSO is tested as an effective improved PSO for getting preferable results on many problems. In this paper, we introduce a chaotic operator into QPSO for further enhancing its global and local searching abilities. The experiments results show that, compared with the other PSOs, our algorithm gets more efficient results. It could be applied in more complex real world problems in our future work.

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Acknowledgments

The authors acknowledge support from the National Nature Science Foundation of China (Nos. 61571236, 61533010, 61602255 and 61320106008), the Macau Science and Technology Fund (FDCT 093/2014/A2, 008/2013/A1), the Research Committee of University of Macau (MYRG2015-00011-FST, MYRG2015-00012-FST).

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Authors and Affiliations

  1. The College of Automation, Nanjing University of Posts and Telecommunications, Nanjing, China

    Zhenghua Wu, Dongmei Wu & Hao Gao

  2. Beijing Institute of Control Engineering, Beijing, China

    Haidong Hu

  3. State Grid Guzhen Electric Power Company, Bengbu, China

    Chuangye Wang

Authors
  1. Zhenghua Wu
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  2. Dongmei Wu
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  3. Haidong Hu
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  4. Chuangye Wang
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  5. Hao Gao
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Corresponding author

Correspondence to Dongmei Wu .

Editor information

Editors and Affiliations

  1. Nanjing University of Posts and Telecommunications, Nanjing, China

    Dong Yue

  2. Shanghai University , Shanghai, China

    Chen Peng

  3. Shanghai University , Shanghai, China

    Dajun Du

  4. Nanjing University of Posts and Telecommunications, Nanjing, China

    Tengfei Zhang

  5. Shanghai University , Shanghai, China

    Min Zheng

  6. Swinburne University of Technology, Melbourne, Victoria, Australia

    Qinglong Han

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Wu, Z., Wu, D., Hu, H., Wang, C., Gao, H. (2017). A New Quantum-Behaved Particle Swarm Optimization with a Chaotic Operator. In: Yue, D., Peng, C., Du, D., Zhang, T., Zheng, M., Han, Q. (eds) Intelligent Computing, Networked Control, and Their Engineering Applications. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 762. Springer, Singapore. https://doi.org/10.1007/978-981-10-6373-2_17

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  • DOI: https://doi.org/10.1007/978-981-10-6373-2_17

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6372-5

  • Online ISBN: 978-981-10-6373-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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