A Comprehensive Study of Parameters Analysis for Galactic Swarm Optimization

The galactic swarm optimization algorithm is a metaheuristic approach inspired by the motion and behavior of stars galaxies. It framework that can use basic search methods. method, which has two-phase structure, performs exploration in first phase exploitation second phase. GSO tries to find best solution space repeating these two phases for specified number times. In this study, analysis maximum epoch (EPmax), iterations phase, parameters, determine balance was performed. 15 different parameter sets consisting values three parameters were created. methods with performed at 30 independent runs. analyzed using 26 benchmark functions.  The functions are tested 30, 60, 100 dimensions. Detailed results presented study obtained also evaluated statistically.