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  • Chen, Hanning  (2)
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  • 1
    Online Resource
    Online Resource
    Hindawi Limited ; 2022
    In:  Discrete Dynamics in Nature and Society Vol. 2022 ( 2022-8-28), p. 1-12
    In: Discrete Dynamics in Nature and Society, Hindawi Limited, Vol. 2022 ( 2022-8-28), p. 1-12
    Abstract: Aiming at the shortcomings of the Harris hawks optimization algorithm (HHO), such as poor initial population diversity, slow convergence speed, poor local optimization ability, and easily falling into local optimum, a Harris hawks optimization algorithm (CCCHHO) integrating multiple mechanisms is proposed. First, the population diversity is enhanced by the initialization of the chaotic method. Second, the cosine function is used to better simulate the characteristics of the periodic change of the energy of the prey in the repeated contests with the group of hawks, to better balance the exploration and exploitation of the algorithm. Third, Cauchy mutation on the optimal individual in the exploration phase is performed, and the characteristics of the Cauchy distribution to enhance the diversity of the population are used, which can effectively prevent the algorithm from falling into the local optimum. Fourth, the local optimization ability of the algorithm by using the ergodicity of the chaotic system in the exploitation phase to perform a chaotic local search for the optimal individual is enhanced, which can effectively jump out after the algorithm falls into the local optimum. Finally, we use the elite individuals of the population to guide the position update of the population’s individuals, fully communicate with the dominant individuals, and speed up the convergence speed of the algorithm. Through the simulation experiments on CCCHHO with 11 different benchmark functions, CCCHHO is better than the gray wolf optimization algorithm (GWO), the Salp swarm algorithm (SSA), the ant lion optimization algorithm (ALO), and three improved HHO algorithms in terms of convergence speed and optimization accuracy, whether it is a unimodal benchmark function or a multimodal benchmark function. The experimental results show that CCCHHO has excellent algorithm efficiency and robustness.
    Type of Medium: Online Resource
    ISSN: 1607-887X , 1026-0226
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2033014-5
    SSG: 11
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  • 2
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2019
    In:  EURASIP Journal on Wireless Communications and Networking Vol. 2019, No. 1 ( 2019-12)
    In: EURASIP Journal on Wireless Communications and Networking, Springer Science and Business Media LLC, Vol. 2019, No. 1 ( 2019-12)
    Type of Medium: Online Resource
    ISSN: 1687-1499
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2019
    detail.hit.zdb_id: 2168613-0
    Location Call Number Limitation Availability
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