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

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.

Automated summary

This review paper provides an in-depth overview of the JAYA algorithm, analyzing its optimization model, convergence characteristics, and various versions. It also discusses the applications and open sources code of the algorithm, highlighting its advantages and limitations in dealing with optimization problems. Finally, the paper suggests possible future enhancements to improve the performance of the JAYA algorithm.