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Research on Magnetotactic Bacteria Optimization Algorithm Based on the Best Individual

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Book cover Bio-Inspired Computing - Theories and Applications

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 472))

Abstract

An improved magnetotactic bacteria optimization algorithm (MBOA) is researched based on the best individual and the performance effect of parameter settings is studied in order to show which setting is more suitable for solving optimization problems. It is tested on four standard function problems and compared with DE, ABC. Experiment results show that MBOAs with different parameter settings are effective for solving most of the benchmark functions. And they do show different performance on a few benchmark functions.

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References

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Author information

Authors and Affiliations

  1. Automation College, Harbin Engineering University, Harbin, 150001, China

    Hongwei Mo, Lili Liu, Lifang Xu & Yanyan Zhao

Authors
  1. Hongwei Mo
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  2. Lili Liu
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  3. Lifang Xu
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  4. Yanyan Zhao
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Editor information

Editors and Affiliations

  1. Huazhong University of Science and Technology, 430074, Wuhan, China

    Linqiang Pan

  2. Institute of Mathematics of the Romanian Academy, 014700, Bucuresti, Romania

    Gheorghe Păun

  3. Department of Computer Science and Artificial Intelligence, University of Sevilla, Avda. Reina Mercedes s/n., 41012, Sevilla, Spain

    Mario J. Pérez-Jiménez

  4. School of Automation, Huazhong University of Science and Technology, 430074, Wuhan, China

    Tao Song

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© 2014 Springer-Verlag Berlin Heidelberg

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Mo, H., Liu, L., Xu, L., Zhao, Y. (2014). Research on Magnetotactic Bacteria Optimization Algorithm Based on the Best Individual. In: Pan, L., Păun, G., Pérez-Jiménez, M.J., Song, T. (eds) Bio-Inspired Computing - Theories and Applications. Communications in Computer and Information Science, vol 472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45049-9_52

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  • DOI: https://doi.org/10.1007/978-3-662-45049-9_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45048-2

  • Online ISBN: 978-3-662-45049-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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