The cooperation of candidate solutions vortex search for numerical function optimization

Abstract

This study presents the cooperation of candidate solutions vortex search called CVS that has been used for solving numerical function optimization. The main inspiration of CVS is that there have been some drawbacks of the Vortex Search (VS) algorithm. Although, the results from the proposal of VS are presented with a high ability but it could produce some drawbacks in updating the positions of vortex swarm. The VS used only single center generating the candidate solutions. The disadvantages happened when VS suffers from multi-modal problems that contain a number of local minima points. To overcome these drawbacks, the proposed CVS generated some cooperation of swarms which created from the diverse points. The experiments were conducted on 12 of benchmark functions. The capability of CVS was compared among the 5 algorithms: DE, GWO, MFO, VS and MVS. The results showed that CVS outperformed all of the comparisons of algorithms used.