On the hybridization of the artificial Bee Colony and Particle Swarm Optimization Algorithms
Mohammed El-Abd · 2012
In this paper we investigate the hybridization of two swarm intelligence algorithms; namely, the Artificial Bee Colony Algorithm (ABC) and Particle Swarm Optimization (PSO). The hybridization technique is a component-based one, where the PSO algorithm is augmented with an ABC component to improve the personal bests of the particles. Three different versions of the hybrid algorithm are tested in this work by experiment-ing with different selection mechanisms for the ABC component. All the algorithms are applied to the well-known CEC05 benchmark functions and compared based on three dif-ferent metrics, namely, the solution reached, the success rate, and the performance rate. 1