Magnetotactic Bacteria Algorithm for Function Optimization

Abstract

Magnetotactic bacteria is a kind of polyphyletic group of prokaryotes with the characteristics of magnetotaxis that make them orient and swim along geomagnetic field lines. A magnetotactic bacteria optimization algorithm(MBOA) inspired by the characteristics of magnetotactic bacteria is researched in the paper. Experiment results show that the MBOA is effective in function optimization problems and has good and competitive performance compared with the other classical optimization algorithms.

Share and Cite:

H. Mo and L. Xu, "Magnetotactic Bacteria Algorithm for Function Optimization," Journal of Software Engineering and Applications, Vol. 5 No. 12B, 2012, pp. 66-71. doi: 10.4236/jsea.2012.512B014.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] L. N. De Castro, F. J. Von Zuben. “Learning and Opti-mization Using the Clonal Selection Principle,” IEEE Trans. on Evolutionary Computation, Vol.6,No.3, pp.239–251, 2002. doi: 10.1109/TEVC.2002.1011539
[2] M. Dorigo, V. Mania-niezzo, A. Colorni. “The Ant System: Optimization by a Colony of Cooperating Agents,” IEEE Trans.Sys. Man and Cybernetics, Vol.26, No.1,pp. 1-13. doi:10.1109/3477.484436
[3] R. E. Dunin-Borkowski, M. R. McCartney, R. B. Frankel, D. A. Bazylinski, M. Posfai, P. R Buseck. “Magnetic Microstructure of Magnetotactic Bacteria by Electron Holography,” Science, Vol. 282, 1998, pp.1868-1870. doi:10.1126/science.282.5395.1868
[4] D. Karaboga, B. Akay. “A Comparative Study of Artificial Bee Colony Algorithm,” Applied Mathematics and Computation, Vol 214, No.1,2009, pp.108–132. doi: 10.1016/j.amc.2009.03.090
[5] J. Kennedy, R. Eber-hart. Particle swarm optimization. IEEE Int Conf on Neural Networks. Piscataway, NJ, 1995,pp.1942-1948. doi:10.1109/ICNN.1995.488968
[6] S. Müeller, J. Mar-chetto, S. Airaghi, P. Koumoutsakos. “Optimization Based on Bacterial Chemotaxis,” IEEE Trans on Evolu-tionary Computation, Vol.6, No.1,2002, pp.16-29. doi:10.1109/4235.985689
[7] A. P. Philipse, D. Maas. “Magnetic Colloids from Magnetotactic Bacteria: Chain Formation and Colloidal Stability,” Langmuir, Vol.18, 2002,pp.9977-9984. doi:10.1021/la0205811
[8] D. Simon. “Biogeogra-phy-based Optimization,” IEEE Trans on Evolutionary Computation, Vol. 12, 2008, pp.702-713.doi:10.1109/TEVC.2008.919004
[9] Mo Hongwei, “Research on Magnetotactic Bacteria Optimi-zation Algorithm,” The Fifth International Conference on Advanced Computational Intelli-gence,Nanjing,Oct,2012,pp.417-422.
[10] M. H. N. Tayarani, T. Akbarzadeh. “Magnetic Optimization Algo-rithms A New Synthesis,” in Proc. of IEEE Congress on Evolutionary Computation. Hong Kong, China, 1-6,June,2008,pp. 2659-2665. doi:10.1109/CEC.2008.4631155
[11] M. Winklhofer, L. G. Abra?ado, A. F. Davila, C. N. Keim, H. G. Lins de Barros. P. “Magnetic Optimization in A Multicellular Mag-netotactic Organism,” Biophysical Journal, Vol 92, 2007,pp. 661-670. doi:10.1529/biophysj.106.093823
[12] V. Tereshko. “Reac-tion–diffusion Model of A Honeybee Colony’s Foraging Behaviour,” in Parallel Problem Solving from Nature VI, Lecture Notes in Computer Science, Vol. 1917, Sprin-ger–Verlag, Berlin, 2000,pp. 807–816. doi:10.1007/3-540-45356-3_79

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.