Zitar Raed Abu, Al-Betar Mohammed Azmi, Awadallah Mohammed A, Doush Iyad Abu, Assaleh Khaled
Sorbonne University Center of Artificial Intelligence, Sorbonne University-Abu Dhabi, Abu Dhabi, UAE.
Artificial Intelligence Research Center (AIRC), College of Engineering and Information Technology, Ajman University, Ajman, UAE.
Arch Comput Methods Eng. 2022;29(2):763-792. doi: 10.1007/s11831-021-09585-8. Epub 2021 May 27.
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.
在这篇综述论文中,对JAYA算法进行了深入概述,它是一种最新的基于种群的算法。JAYA算法结合了进化算法中的适者生存原则以及群体智能方法对全局最优解的吸引力。首先,仔细分析了JAYA算法的优化模型和收敛特性。此后,对JAYA算法的改进版本进行了调研,如改进型、二进制型、混合型、并行型、混沌型、多目标型等。还基于几个问题领域讨论并总结了使用JAYA算法相关版本解决的各种应用。此外,确定了JAYA算法的开源代码,为JAYA研究社区提供丰富资源。对JAYA算法的批判性分析揭示了其在处理优化问题时的优点和局限性。最后,论文以结论和为提高JAYA算法性能而建议的可能的未来改进措施结尾。本综述的读者将确定JAYA算法使用的最佳领域和应用,并能证明他们与JAYA相关的贡献。