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Erschienen in:
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2021 | OriginalPaper | Buchkapitel

Jaya Algorithm and Applications: A Comprehensive Review

verfasst von : Essam H. Houssein, Ahmed G. Gad, Yaser M. Wazery

Erschienen in: Metaheuristics and Optimization in Computer and Electrical Engineering

Verlag: Springer International Publishing

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Abstract

All the population-based optimization algorithms are probabilistic algorithms and require only a few control parameters including number of candidates, number of iterations, elite size, etc. Besides these control parameters, algorithm-specific control parameters are required by different algorithms. Either the computational effort is increased or the local optimal solution is yielded as a result of the improper tuning of algorithm-specific parameters. Thus, the algorithm which works without any algorithm-specific parameters such as Jaya Algorithm (JA) is widespread among the optimization applications and researchers. JA can be easily implemented based on not having to tune any algorithm-specific parameters. In order to prove that JA could be applied to every problem arising in practice, this study presents a comprehensive review of the advances with JA and its variants. On the other hand, the performance of JA was evaluated to solve the Himmelblau function against five well-known optimization algorithms. Therefore, this study is expected to highlight the JA’s capabilities and performances especially for those researchers who are eager to explore the algorithm.

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Metadaten
Titel
Jaya Algorithm and Applications: A Comprehensive Review
verfasst von
Essam H. Houssein
Ahmed G. Gad
Yaser M. Wazery
Copyright-Jahr
2021
Buch
Metaheuristics and Optimization in Computer and Electrical Engineering

Print ISBN: 978-3-030-56688-3

Electronic ISBN: 978-3-030-56689-0

Copyright-Jahr: 2021

DOI
https://doi.org/10.1007/978-3-030-56689-0_2

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