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Harris Hawks Optimization Algorithm: Variants and Applications
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DOI：10.1007/s11831-022-09780-1.png)
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Abstract
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This paper introduces a comprehensive survey of a new swarm intelligence optimization algorithm so-called Harris hawks optimization (HHO) and analyzes its major features. HHO is counted as an example of the most effective Optimization algorithm and utilized in different problems in various domains, successfully. For example, energy and Power Flow, engineering, medical applications, networks, and image processing. This review introduces the available related works of HHO where the main topics include; HHO variants, modification, and Hybridization, HHO applications, analysis and differentiation between HHO and other algorithms in the literature. Finally, the conclusions concentrate on the existing work on HHO, showing its disadvantages, and propose future works. The review paper will be helpful for the researchers and practitioners of HHO belonging to a wide range of audiences from the domains of optimization, engineering, medical, data mining and clustering. As well, it is wealthy in research on health, environment and public safety. Also, it will aid those who are interested by providing them with potential future research.
Keywords:
CUCKOO SEARCH ALGORITHM
PARTICLE SWARM OPTIMIZATION
DIFFERENTIAL EVOLUTION
GLOBAL OPTIMIZATION
SYSTEM
PLACEMENT
MODEL
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12.1
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1.8K
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1.2W
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