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A Novel BCC Algorithm for Function Optimization

  • Jia-Ze Sun
  • Guo-Hua Geng
  • Ming-Quan Zhou
  • Wang Shu-Yan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 107)

Abstract

Aiming at improving the performance of bacterial colony chemotaxis (BCC) optimization algorithm, a novel bacterial colony chemotaxis algorithm is introduced through integrating chaotic optimization into bacterial colony chemotaxis (NBCC) optimization algorithm, it greatly enhances the local searching efficiency and global searching performance. Simulation results on standard test functions show that NBCC is pretty efficient to solve complex problems.

Keywords

Bacterial colony chemotaxis Function optimization Kent map 

Notes

Acknowledgments

This work was supported in part by project “ Research on Key Problem of Combinatorial Software Testing optimization Based on Swarm Intelligence” (61050003) from National Natural Science Foundation of China, by project “Smart Combinatorial Soft Testing method “ (ZL2009-9) from Natural Science Foundation of XUPT,by project “Smart Combinatorial Embedded Soft Testing Platform” (2009K08-26) from Key Technologies R&D Programmed Foundation of Shan xi Province.

References

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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Jia-Ze Sun
    • 1
    • 2
  • Guo-Hua Geng
    • 2
  • Ming-Quan Zhou
    • 3
  • Wang Shu-Yan
    • 1
  1. 1.School of Computer Science and TechnologyXi’an University of Post and TelecommunicationsXi’anChina
  2. 2.Institute of Visualization TechnologyNorthwest UniversityXi’anChina
  3. 3.School of Information Science and TechnologyBeijing Normal UniversityBeijingChina

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