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Brain Storm Optimization Algorithm

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Advances in Swarm Intelligence (ICSI 2011)

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

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Abstract

Human being is the most intelligent animal in this world. Intuitively, optimization algorithm inspired by human being creative problem solving process should be superior to the optimization algorithms inspired by collective behavior of insects like ants, bee, etc. In this paper, we introduce a novel brain storm optimization algorithm, which was inspired by the human brainstorming process. Two benchmark functions were tested to validate the effectiveness and usefulness of the proposed algorithm.

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Author information

Authors and Affiliations

  1. Xi’an Jiaotong-Liverpool University, Suzhou, China, 215123

    Yuhui Shi

Authors
  1. Yuhui Shi
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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

Shi, Y. (2011). Brain Storm Optimization Algorithm. 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_36

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  • DOI: https://doi.org/10.1007/978-3-642-21515-5_36

  • 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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