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New chaotic flower pollination algorithm for unconstrained non-linear optimization functions

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Abstract

Flower pollination algorithm (FPA) is susceptible to local optimum and substandard precision of calculations. Chaotic operator (CO), which is used in local algorithms to optimize the best individuals in the population, can successfully enhance the properties of the flower pollination algorithm. A new chaotic flower pollination algorithm (CFPA) has been proposed in this work. Further FPA and its four proposed variants by using different chaotic maps are tested on nine mathematical benchmark functions of high dimensions. Proposed variants of CFPA are CFPA1, CFPA2, CFPA3 and CFPA4. The result of the experiment indicates that the proposed chaotic flower pollination variant CFPA2 could increase the precision of minimization of function value and CPU time to run an algorithm.

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Authors and Affiliations

  1. USICT, GGSIPU, New Delhi, India

    Arvinder Kaur & Amrit Pal Singh

  2. SAG, DRDO, New Delhi, India

    Saibal K. Pal

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  1. Arvinder Kaur
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  2. Saibal K. Pal
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  3. Amrit Pal Singh
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Correspondence to Amrit Pal Singh.

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Kaur, A., Pal, S.K. & Singh, A.P. New chaotic flower pollination algorithm for unconstrained non-linear optimization functions. Int J Syst Assur Eng Manag 9, 853–865 (2018). https://doi.org/10.1007/s13198-017-0664-y

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  • DOI: https://doi.org/10.1007/s13198-017-0664-y

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