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Alternated Chaotic Biogeography Based Algorithm for Optimization Problems

Author

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  • Mamta Rani

    (Central University of Rajasthan, Ajmer, India)

  • Deepak Kumar

    (Central University of Rajasthan, Ajmer, India)

Abstract

Chaotic maps have improved the performance of BBO algorithm as chaotic migration and chaotic mutation help in maintaining diversity of the population on a higher level to avoid a habitat's entrapment in the local optimal solutions. Many chaotic maps have been used in BBO algorithm. Recently, alternation method in discrete dynamics has emerged as a powerful tool for control and anti-control of chaos. In this article, it is proposed to use alternated chaotic logistic map in BBO algorithm to improve the performance further.

Suggested Citation

  • Mamta Rani & Deepak Kumar, 2019. "Alternated Chaotic Biogeography Based Algorithm for Optimization Problems," International Journal of Applied Evolutionary Computation (IJAEC), IGI Global, vol. 10(4), pages 39-50, October.
    • Handle: RePEc:igg:jaec00:v:10:y:2019:i:4:p:39-50
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJAEC.2019100102
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    Cited by:

    1. Xing, Aosheng & Chen, Yong & Suo, Jinyi & Zhang, Jie, 2024. "Improving teaching-learning-based optimization algorithm with golden-sine and multi-population for global optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 221(C), pages 94-134.
    2. Kumar, Deepak & Rani, Mamta, 2022. "Alternated superior chaotic variants of gravitational search algorithm for optimization problems," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).

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