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Group Search Optimizer with Interactive Dynamic Neighborhood

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Artificial Intelligence and Computational Intelligence (AICI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7004))

Abstract

Group search optimizer(GSO) is a new novel optimization algorithm by simulating animal behaviour. It uses the Gbest topology structure, which leads to rapid exchange of information among particles. So,it is easily trapped into a local optima when dealing with multi-modal optimization problems. In this paper,inspiration from the Newman and Watts model,a improved group search optimizer with interactive dynamic neighborhood (IGSO) is proposed. Adopting uniform design and the linear regression method on the parameter selection, four benchmark functions demonstrate the effectiveness of the algorithm.

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Author information

Authors and Affiliations

  1. Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan, China

    Guohua He, Zhihua Cui & Jianchao Zeng

Authors
  1. Guohua He
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  2. Zhihua Cui
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  3. Jianchao Zeng
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Editor information

Editors and Affiliations

  1. School of Business Information Technology, RMIT University, City Campus, 124 La Trobe Street, 3000, Melbourne, VIC, Australia

    Hepu Deng

  2. School of Electronics and Information, Tongji University, 201804, Shanghai, China

    Duoqian Miao

  3. School of Computer and Information Engineering, Shanghai University of Electric Power, 200090, Shanghai, China

    Jingsheng Lei

  4. Department of Business Administration, Caritas Institute of Higher Education, 18 Chui Ling Road, Tseung Kwan O, Hong Kong, China

    Fu Lee Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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He, G., Cui, Z., Zeng, J. (2011). Group Search Optimizer with Interactive Dynamic Neighborhood. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7004. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23896-3_25

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  • DOI: https://doi.org/10.1007/978-3-642-23896-3_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23895-6

  • Online ISBN: 978-3-642-23896-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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