Quick artificial bee colony algorithm with symbiotic search strategy for global optimization

Artificial bee colony (ABC) is a metaheuristic algorithm (MHA) which has received extensive attention. However, it often suffers from unsatisfactory exploitation. On the other hand, symbiosis organisms search (SOS) is a MHA which has good exploitation ability due to its mutualism search operator. In this paper, we employ the mutualism search operator to enhance the ABC's exploitation ability, and thus propose a hybrid quick ABC algorithm with symbiotic search strategy (qABCSS). The performance of qABCSS is comprehensively compared with well-established SOS, ABC and other metaheuristic algorithms using the CEC2014 function. Experimental results demonstrate the superiority of qABCSS in terms of solution accuracy and convergence, indicating the effectiveness of the hybridization.