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On the Farther Analysis of Performance of the Artificial Searching Swarm Algorithm

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Book cover Advances in Swarm Intelligence (ICSI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6145))

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Abstract

Artificial Searching Swarm Algorithm (ASSA) is an intelligent optimization algorithm, and its performance has been analyzed and compared with some famous algorithms. For farther understanding the running principle of ASSA, this work discusses the functions of three behavior rules which decide the moves of searching swarm. Some typical functions are selected to do the simulation tests. The function simulation tests showed that the three behavior rules are indispensability and endow the ASSA with powerful global optimization ability together.

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Author information

Authors and Affiliations

  1. Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, Hebei University of Technology, Tianjin, China

    Tanggong Chen, Lijie Zhang & Lingling Pang

Authors
  1. Tanggong Chen
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  2. Lijie Zhang
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  3. Lingling Pang
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Department of Machine Intelligence, Peking University, 100871, Beijing, China

    Ying Tan

  2. Research and Postgraduate Office, Xi’an Jiaotong-Liverpool University, 215123, Suzhoum, China

    Yuhui Shi

  3. Department of Electrical and Computer Engineering, National University of Singapore, Engineering Drive 3, 4 Engineering Drive 3, 117576, Singapore

    Kay Chen Tan

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© 2010 Springer-Verlag Berlin Heidelberg

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Chen, T., Zhang, L., Pang, L. (2010). On the Farther Analysis of Performance of the Artificial Searching Swarm Algorithm. In: Tan, Y., Shi, Y., Tan, K.C. (eds) Advances in Swarm Intelligence. ICSI 2010. Lecture Notes in Computer Science, vol 6145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13495-1_5

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  • DOI: https://doi.org/10.1007/978-3-642-13495-1_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13494-4

  • Online ISBN: 978-3-642-13495-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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