| Summary: | This paper proposes a novel performance enhanced Jaya algorithm with a two group adaption (E-Jaya). Two improvements are presented in E-Jaya. First, instead of using the best and the worst values in Jaya algorithm, E-Jaya separates all candidates into two groups: the better and the worse groups based on their fitness values, then the mean of the better group and the mean of the worse group are used. Second, in order to add non algorithm-specific parameters in E-Jaya, a novel adaptive method of dividing the two groups has been developed. Finally, twelve benchmark functions with different dimensionality, such as 40, 60, and 100, were evaluated using the proposed E-Jaya algorithm. The results show that E-Jaya significantly outperformed Jaya algorithm in terms of the solution accuracy. Additionally, E-Jaya was also compared with a differential evolution (DE), a self-adapting control parameters in differential evolution (jDE), a firefly algorithm (FA), and a standard particle swarm optimization 2011 (SPSO2011) algorithm. E-Jaya algorithm outperforms all the algorithms.
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