Nothing Special   »   [go: up one dir, main page]

Skip to main content
Log in

A novel chaos optimization algorithm

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

In this paper, by analyzing the best chaotic sequences generated by sixteen different chaotic maps, a novel chaos optimization algorithm is presented. It can intelligently base on different chaotic maps to select different strategies so as to map the chaotic variables into the optimization variables. For the proposed algorithm, the obtained best values, the run time, and the role of the first and the second stage search by using different chaotic maps are also analyzed and compared. The simulation results implemented on several classic test functions demonstrate that the proposed algorithm has a high performance and an outstanding efficiency.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Cheng ZG et al (2007) Chaotic hybrid particle swarm optimization algorithm based on tent map[J]. Syst Eng Electron 29(1):103–106

    MATH  Google Scholar 

  2. Erramilli A, Singh RP, Pruthi P (1994) Modeling packet traffic with chaotic maps[M]. Citeseer

  3. Feldman DP (2012) Chaos and fractals: an elementary introduction[M]. Oxford University Press

  4. Fister I Jr et al (2015) A review of chaos-based firefly algorithms: perspectives and research challenges[J]. Appl Math Comput 252(1):155–165

    MathSciNet  MATH  Google Scholar 

  5. Gandomi AH et al (2013) Firefly algorithm with chaos[J]. Commun Nonlinear Sci Numer Simul 18(1):89–98

    Article  MathSciNet  MATH  Google Scholar 

  6. May RM (1976) Simple mathematical models with very complicated dynamics[J]. Nature 261(5560):459–467

    Article  Google Scholar 

  7. Mingjun J, Tang H (2004) Application of chaos in simulated annealing[J]. Chaos, Solitons Fractals 21(4):933–941

    Article  MATH  Google Scholar 

  8. Shayeghi H et al (2010) Multi-machine power system stabilizers design using chaotic optimization algorithm[J]. Energy Convers Manag 51(7):1572–1580

    Article  Google Scholar 

  9. Tavazoei MS, Haeri M (2007) Comparison of different one-dimensional maps as chaotic search pattern in chaos optimization algorithms[J]. Appl Math Comput 187(2):1076–1085

    MathSciNet  MATH  Google Scholar 

  10. Tomida AG (2008) Matlab toolbox and GUI for analyzing one-dimensional chaotic maps[C]. Int Conf Comput Sci Its Appl (ICCSA’08). 321–330: IEEE Comput Soc

  11. Wu Z Chen Z (1996) Introduction of Chaos theory[M]: Shanghai Science and Technology, Bibliographic Publishing House

  12. Yan H et al. (2014) Chaos genetic algorithm optimization design based on linear motor[C]. 2014 17th Int Conf Electrical Mach Syst (ICEMS): 2265–2268: IEEE

  13. Yantao L, Shaojiang D, Di X (2011) A novel Hash algorithm construction based on chaotic neural network[J]. Neural Comput & Applic 20(1):133–141

    Article  Google Scholar 

  14. Yuan X et al (2014) Hybrid parallel chaos optimization algorithm with harmony search algorithm[J]. Appl Soft Comput 17:12–22

    Article  Google Scholar 

  15. Zhang J, Yang Y, Zhang Q (2009) The particle swarm optimization algorithm based on dynamic chaotic perturbations and its application to K-means[C]. 2009 Int Conf Comput Intell Security(CIS 2009). 2009: p. 282–286. Beijing, China: IEEE Computer Society

  16. Zhao D, He Y (2015) Chaotic binary bat algorithm for analog test point selection[J]. Analog Integ Circ Signal Process: 1–14

Download references

Acknowledgments

This research was supported by Guangxi Universities Key Project of Science and Technology Research (No.KY2015ZD099), Guangxi Natural Science Foundation (No.2014GXNSFBA118268,2014GXNSFBA118010), Scientific Research Staring Foundation for the PHD Scholars of Yulin Normal University (No.G2014005), Key Project of Yulin Normal University (No.2014YJZD05), and Open Foundation for Guangxi Colleges and Universities Key Lab of Complex System Optimization and Big Data Processing (No. 2015CSOBDP0301,2015CSOBDP0303).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Jie Zhang or Xiaoshu Zhu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Feng, J., Zhang, J., Zhu, X. et al. A novel chaos optimization algorithm. Multimed Tools Appl 76, 17405–17436 (2017). https://doi.org/10.1007/s11042-016-3907-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-016-3907-z

Keywords

Navigation