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Applying modified cuckoo search algorithm for solving systems of nonlinear equations

  • Xinming Zhang
  • Qian Wan
  • Youhua Fan
Original Article

Abstract

In the present paper, a modified cuckoo search algorithm is proposed for solving nonlinear equations, that is, the niche cuckoo search algorithm (NCSA) based on fitness-sharing principle. Niche strategy is introduced to enhance the ability of the cuckoo search algorithm to solve nonlinear equations. So as to evaluate the efficiency of NCSA, NCSA has been first benchmarked by twenty standard test functions by comparing with standard genetic algorithm, chaos gray-coded genetic algorithm and standard cuckoo search algorithm. Then, solutions for several examples of nonlinear systems are presented and compared with results obtained by other approaches. Moreover, the sensitivity analysis of the method to initial interval, nests number, probability and niche number has been studied. Comparison results reveal that the proposed algorithm can cope with the highly nonlinear problems and outperforms many algorithms which exist in the literature.

Keywords

Nonlinear equations systems Cuckoo search algorithm Niche strategy Fitness-sharing principle 

Notes

Acknowledgements

This study was funded by the National Science Foundation of China (Grant No. 41004052).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© The Natural Computing Applications Forum 2017

Authors and Affiliations

  1. 1.Shenzhen Graduate SchoolHarbin Institute of TechnologyShenzhenChina

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