ReviewArchives of computational methods in engineering : state of the art reviews2022
An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications.
Review in Archives of computational methods in engineering : state of the art reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Article
- Optimization design of brushless DC motor based on improved JAYA algorithm.Scientific reports · 2024Article
- Development of renewable energy fed three-level hybrid active filter for EV charging station load using Jaya grey wolf optimization.Scientific reports · 2024Article
- Explainable artificial intelligence approaches for COVID-19 prognosis prediction using clinical markers.Scientific reports · 2024Article
- Artificial intelligence for diagnosis of mild-moderate COVID-19 using haematological markers.Annals of medicine · 2023Article
- A Novel Bio-Inspired Optimization Algorithm Design for Wind Power Engineering Applications Time-Series Forecasting.Biomimetics (Basel, Switzerland) · 2023Article
- Review and analysis for the Red Deer Algorithm.Journal of ambient intelligence and humanized computing · 2023Article
- Adaptive frequency control in smart microgrid using controlled loads supported by real-time implementation.PloS one · 2023Article
- Graph drawing using Jaya.PloS one · 2023Article
- Integrated Development of Artificial Intelligence and Economic Management.Computational intelligence and neuroscience · 2022Article
- Recent advances of bat-inspired algorithm, its versions and applications.Neural computing & applications · 2022Review
- A Review of Reservoir Operation Optimisations: from Traditional Models to Metaheuristic Algorithms.Archives of computational methods in engineering : state of the art reviews · 2022Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this review paper, JAYA algorithm, which is a recent population-based algorithm is intensively overviewed. The JAYA algorithm combines the survival of the fittest principle from evolutionary algorithms as well as the global optimal solution attractions of Swarm Intelligence methods. Initially, the optimization model and convergence characteristics of JAYA algorithm are carefully analyzed. Thereafter, the proposed versions of JAYA algorithm have been surveyed such as modified, binary, hybridized, parallel, chaotic, multi-objective and others. The various applications tackled using relevant versions of JAYA algorithm are also discussed and summarized based on several problem domains. Furthermore, the open sources code of JAYA algorithm are identified to provide enrich resources for JAYA research communities. The critical analysis of JAYA algorithm reveals its advantages and limitations in dealing with optimization problems. Finally, the paper ends up with conclusion and possible future enhancements suggested to improve the performance of JAYA algorithm. The reader of this overview will determine the best domains and applications used by JAYA algorithm and can justify their JAYA-related contributions.
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Registered trials
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