Optimal Weight Design of Spur Gear Using a Modified Jaya Algorithm

Gears are essential components in industrial machinery, and their design needs to be optimized to ensure the proper functioning of mechanical systems across various industrial applications. In this study, an optimization approach is proposed to determine the optimal design of a spur gear. This approach is based on an improved Jaya algorithm, which features a straightforward formulation without any algorithm-specific control parameters. Utilizing a simple and parameter-free updating mechanism, the strength of this algorithm lies in its iterative ability to enhance candidate solutions by moving them toward the best solution while avoiding the worst one, providing a flexible framework for optimization. However, since the original Jaya algorithm was primarily designed for continuous optimization problems, this research incorporates adjustments to adapt it effectively for mixed-variable optimization problems and to manage multi-objective functions. The effectiveness of the proposed algorithm is evaluated through examples of constrained problems taken from previous research and case studies on spur gear design, which were refined in this study. The optimum solutions obtained using the improved Jaya are compared with other metaheuristic optimization algorithms. Results exhibit promising results regarding objective function value, solution robustness, and statistical results.