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Survey of using grasshopper algorithm

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  • Hanaa Mohammed Osman

Abstract

The metaheuristic optimization algorithm is used to explain a large region solution space. One of these algorithms is a grasshopper which divides the search process into exploitation and exploration. This article focuses on research efforts directed at gaining a clear understanding of the behavior of grasshoppers and it is using optimization algorithms. It is concluded that the benefits have been effective in answering global unrestricted and restricted optimization issues, easy development, high accuracy, and obtaining a good solution. However, the disadvantages of the GOA algorithm are simple to fall into local optimum and slow convergence speed.

Suggested Citation

  • Hanaa Mohammed Osman, 2022. "Survey of using grasshopper algorithm," Technium, Technium Science, vol. 4(1), pages 37-44.
    • Handle: RePEc:tec:techni:v:4:y:2022:i:1:p:37-44
    DOI: 10.47577/technium.v4i3.6344
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    References listed on IDEAS

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    1. Bustani Hadi Wijaya & Ramadhani Kurniawan Subroto & Kuo Lung Lian & Nanang Hariyanto, 2020. "A Maximum Power Point Tracking Method Based on a Modified Grasshopper Algorithm Combined with Incremental Conductance," Energies, MDPI, vol. 13(17), pages 1-19, August.
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    Cited by:

    1. Nadia Mohammed Majeed, 2022. "Implementation of Features Selection Based on Dragonfly Optimization Algorithm," Technium, Technium Science, vol. 4(1), pages 44-52.

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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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