Directed jaya algorithm for delivering nano-robots to cancer area

Ezzat, Doaa; Amin, Safaa; Shedeed, Howida A.; Tolba, Mohamed F.

doi:10.1080/10255842.2020.1797698

Cited by 6 publications

(1 citation statement)

References 16 publications

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“…In [109], the authors combined the JAYA algorithm with directed particle swarm optimization (DPSO) for delivering nano-robots to cancer areas. Their algorithm is named Directed Jaya (DJaya) algorithm.…”

Section: Hybridization With Swarm-based Algorithmsmentioning

confidence: 99%

An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications

Zitar

Al-Betar

Awadallah

et al. 2021

Arch Computat Methods Eng

125

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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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Section: Hybridization With Swarm-based Algorithmsmentioning

confidence: 99%