Introducing a socio-inspired swarm intelligence algorithm for numerical function optimization

Abstract

Swarm intelligence algorithms have been successfully applied as optimization tools in various applications, such as biology, commerce, and engineering. This paper presents BRADO (BRAin Drain Optimization) algorithm as a new socio-inspired swarm intelligence approach, in which the search algorithm is inspired by the process of brain drain phenomenon. In order to evaluate the BRADO performance, it was applied to several benchmark optimization functions and the results produced by BRADO, particle swarm optimization, imperialist competitive algorithm and GA have been compared. Our findings show the BRADO superiority to avoid the regions around local minima and dealing with high dimensionality problems.