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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 19/2020

22.07.2020 | Review

A comprehensive survey of the Grasshopper optimization algorithm: results, variants, and applications

verfasst von: Laith Abualigah, Ali Diabat

Erschienen in: Neural Computing and Applications | Ausgabe 19/2020

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Abstract

The grasshopper optimization algorithm is one of the dominant modern meta-heuristic optimization algorithms. It has been successfully applied to various optimization problems in several fields, including engineering design, wireless networking, machine learning, image processing, control of power systems, and others. We survey the available literature on the grasshopper optimization algorithm, including its modifications, hybridizations, and generalization to the binary, chaotic, and multi-objective cases. We review its applications, evaluate the algorithms, and provide conclusions.
Vorheriger Artikel A survey on face data augmentation for the training of deep neural networks
Nächster Artikel Attentive gated neural networks for identifying chromatin accessibility

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Metadaten
Titel
A comprehensive survey of the Grasshopper optimization algorithm: results, variants, and applications
verfasst von
Laith Abualigah
Ali Diabat
Publikationsdatum
22.07.2020
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 19/2020
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-020-04789-8

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