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A power spectrum optimization algorithm inspired by magnetotactic bacteria

Neural Computing and Applications volume 25, pages 1823–1844 (2014)Cite this article

Abstract

Magnetotactic bacteria (MTB) are one kind of bacteria with magnetic particles called magnetosomes in their bodies. These particles often connect together like a chain. The MTB move toward the ideal living conditions under the interaction between magnetic field produced by the magnetic particles chain and that of the earth. In the paper, a new magnetic bacteria algorithm based on power spectrum (PSMBA) for optimization is proposed. The candidate solutions are decided by power spectrum in the algorithm. It mainly includes four steps: power spectrum calculation, bacteria swimming, bacteria rotation and bacteria replacement. The effect of swimming schemes and parameter settings on the performance of PSMBA is studied. And it is compared with GA, PSO and its variants and some other optimization algorithms on 25 benchmark functions including CEC2005. The simulation results show that PSMBA has better performance on most of the problems than most of the compared algorithms.

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Acknowledgments

This work is partially supported by the National Natural Science Foundation of China under Grant No. 61075113, the Excellent Youth Foundation of Heilongjiang Province of China under Grant No. JC201212, the Fundamental Research Funds for the Central Universities No. HEUCFX041306 and Harbin Excellent Discipline Leader, No. 2012RFXXG073.

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Authors and Affiliations

  1. Automation College, Harbin Engineering University, No. 154 Natong Street, Harbin, 150001, China

    Hongwei Mo & Lili Liu

  2. Engineering Training Center, Harbin Engineering University, Harbin, China

    Lifang Xu

Authors
  1. Hongwei Mo
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  2. Lili Liu
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  3. Lifang Xu
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Correspondence to Hongwei Mo.

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Mo, H., Liu, L. & Xu, L. A power spectrum optimization algorithm inspired by magnetotactic bacteria. Neural Comput & Applic 25, 1823–1844 (2014). https://doi.org/10.1007/s00521-014-1672-3

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  • DOI: https://doi.org/10.1007/s00521-014-1672-3

Keywords

  • Magnetic bacteria
  • Power spectrum
  • Optimization
  • Nature-inspired computing