Numerous computational algorithms used for getting high performance for solving mathematics, engineering and statistical complexities. Recently, an attractive bio-inspired method namely: Artificial Bee Colony (ABC), which has been shown outstanding performance with some typical computational algorithms in different complex problems. The modification, hybridization and improvement strategies made ABC more pretty to science and engineering researchers. The two well-known honeybees based upgraded algorithms are: Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS) are used the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. Here, the above GGABC and GABC methods are hybrid called 3G-ABC algorithm for strong discovery and exploitation processes. The experimental results tested with sets of ten numerical benchmark functions. The simulation results show that the proposed 3G-ABC algorithm outperforms PSO, ABC, GABC and GGABC algorithm in most of the experiments of ten benchmarked numerical function optimization.