Parameter Analysis on Fruit Fly Optimization Algorithm

Abstract

Fruit fly algorithm is a novel intelligent optimization algorithm based on foraging behavior of the real fruit flies. In order to find optimum solution for an optimization problem, fixed parameters are obtained as a result of manual test in fruit fly algorithm. In this study, it is aimed to find the optimum solution by analyzing the constant parameter concerning the direction of the algorithm instead of manual defining on initialization stage. The study shows an automated approach for finding the related parameter by utilizing grid search algorithm. According to the experimental results, it can be seen that this approach could be used as an alternative way for finding related parameter or other ones in order to achieve optimum model.