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International Conference in Swarm Intelligence

ICSI 2011: Advances in Swarm Intelligence pp 86–92Cite as

An Adaptive Tribe-Particle Swarm Optimization

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6728))

Abstract

This paper talks about the problems in particle swarm optimization (PSO), including local optimum and difficulty in improving solution accuracy by fine tuning. We presents a new variation of Adaptive Tribe-PSO model where nonlinear updating of inertia weight and a particle’s fitness with Tribe-PSO model are combined to improve the speed of convergence as well as fine tune the search in the multidimensional space. The method proved to be a powerful global optimization algorithm.

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Author information

Authors and Affiliations

  1. Intelligent Systems and Renewable Energy Research Center, Beijing Jiaotong University, China

    Yong Duan Song & Lu Zhang

  2. Chongqing Institute of Science and Technology, China

    Peng Han

Authors
  1. Yong Duan Song
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  2. Lu Zhang
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  3. Peng Han
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, 215123, Suzhou, China

    Yuhui Shi

  3. Automation College, Chongqing University, 400030, Chongqing, China

    Yi Chai

  4. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, 400065, Chongqing, P.R. China

    Guoyin Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Cite this paper

Song, Y.D., Zhang, L., Han, P. (2011). An Adaptive Tribe-Particle Swarm Optimization. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds) Advances in Swarm Intelligence. ICSI 2011. Lecture Notes in Computer Science, vol 6728. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21515-5_11

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  • DOI: https://doi.org/10.1007/978-3-642-21515-5_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21514-8

  • Online ISBN: 978-3-642-21515-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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