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A Modified Standard PSO-2011 with Robust Search Ability

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Bio-inspired Computing: Theories and Applications (BIC-TA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 791))

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Abstract

Standard particle swarm optimization 2011(SPSO2011, takes SPSO for short) was proposed to overcome problems that there is bias of the search area existing in the conventional PSO depending on rotational invariant property. The performance of SPSO is affected by the distribution of the center of the search range and the global search ability fades away during the iteration process. In this paper, in order to reinforce diversity-maintain ability as well as improve local search ability, a modified diversity-guided SPSO (DGAP-MSPSO) algorithm is proposed. A modified SPSO variant with average point method is first applied till the swarm loses its diversity thus to improve local search ability. Then, the search process turns to another new SPSO variant in which an enhanced diversity-maintain operator is used for global search. The DGAP-MSPSO switches alternately between two SPSO variants according to swarm diversity, thus its search ability is improved. Experimental results shows that our proposed algorithm, the DGAP-MSPSO algorithm, gets better performance on most test functions compared with other SPSO variants.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Nos. 61572241 and 61271385), the Foundation of the Peak of Six Talents of Jiangsu Province (No. 2015-DZXX-024), and the Fifth 333 High Level Talented Person Cultivating Project of Jiangsu Province.

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Authors and Affiliations

  1. School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, 212013, Jiangsu, China

    Hongguan Liu & Fei Han

Authors
  1. Hongguan Liu
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  2. Fei Han
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Corresponding author

Correspondence to Hongguan Liu .

Editor information

Editors and Affiliations

  1. School of Automation, Huazhong University of Science and Technology, Wuhan, China

    Cheng He

  2. Automation College, Harbin Engineering University, Harbin, China

    Hongwei Mo

  3. School of Automation, Huazhong University of Science and Technology, Wuhan, China

    Linqiang Pan

  4. Automation College, Harbin Engineering University, Harbin, China

    Yuxin Zhao

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Liu, H., Han, F. (2017). A Modified Standard PSO-2011 with Robust Search Ability. In: He, C., Mo, H., Pan, L., Zhao, Y. (eds) Bio-inspired Computing: Theories and Applications. BIC-TA 2017. Communications in Computer and Information Science, vol 791. Springer, Singapore. https://doi.org/10.1007/978-981-10-7179-9_16

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  • DOI: https://doi.org/10.1007/978-981-10-7179-9_16

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7178-2

  • Online ISBN: 978-981-10-7179-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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