A new metaheuristic for numerical function optimization: Vortex Search algorithm

Abstract

In this study, a new single-solution based metaheuristic, namely the Vortex Search (VS) algorithm, is proposed to perform numerical function optimization. The proposed VS algorithm is inspired from the vortex pattern created by the vortical flow of the stirred fluids. To provide a good balance between the explorative and exploitative behavior of a search, the proposed method models its search behavior as a vortex pattern by using an adaptive step size adjustment scheme. The proposed VS algorithm is tested over 50 benchmark mathematical functions and the results are compared to both the single-solution based (Simulated Annealing, SA and Pattern Search, PS) and population-based (Particle Swarm Optimization, PSO2011 and Artificial Bee Colony, ABC) algorithms. A Wilcoxon-Signed Rank Test is performed to measure the pair-wise statistical performances of the algorithms, the results of which indicate that the proposed VS algorithm outperforms the SA, PS and ABC algorithms while being competitive with the PSO2011 algorithm.