Jaya Algorithm Paralleled with Genetic Algorithm for Two Benchmark Function

This paper describes the Jaya Algorithm and compares its performance with the Genetic Algorithm for optimizing the Himmelblau function and the Rosenbrock function. The Jaya algorithm is designed based on the concept of moving towards the best result and avoiding the worst result. According to the paper, the Jaya Algorithm demonstrated effectiveness and robust behavior compared to the Genetic Algorithm when solving these benchmark functions. To make this comparison, the paper likely evaluated the fitness values and mean values obtained by both algorithms for optimizing the given benchmark functions. Fitness value indicates how close a solution is to the optimal one, and the mean value represents the average performance of the algorithms over multiple iterations or runs. Based on the comparison results, the paper claims that the Jaya algorithm outperforms the Genetic algorithm for the Himmelblau function and the Rosenbrock function. It suggests that the Jaya Algorithm is the superior choice when it comes to optimizing these specific functions.