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Computers 2018, 7(4), 69; https://doi.org/10.3390/computers7040069

Global Gbest Guided-Artificial Bee Colony Algorithm for Numerical Function Optimization

1
College of Computer Science, King Khalid University, Abha 62529, Saudi Arabia
2
School of Mathematics, Thapar Institute of Engineering & Technology (Deemed University) Patiala, Punjab 147004, India
3
Faculty of Computer Science, Universiti Tun Hussein Onn Malaysia, Batu Pahat, Johor 83000, Malaysia
*
Author to whom correspondence should be addressed.
Received: 25 September 2018 / Revised: 28 November 2018 / Accepted: 3 December 2018 / Published: 7 December 2018
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Abstract

Numerous computational algorithms are used to obtain a high performance in solving mathematics, engineering and statistical complexities. Recently, an attractive bio-inspired method—namely the Artificial Bee Colony (ABC)—has shown outstanding performance with some typical computational algorithms in different complex problems. The modification, hybridization and improvement strategies made ABC more attractive to science and engineering researchers. The two well-known honeybees-based upgraded algorithms, Gbest Guided Artificial Bee Colony (GGABC) and Global Artificial Bee Colony Search (GABCS), use the foraging behavior of the global best and guided best honeybees for solving complex optimization tasks. Here, the hybrid of the above GGABC and GABC methods is called the 3G-ABC algorithm for strong discovery and exploitation processes. The proposed and typical methods were implemented on the basis of maximum fitness values instead of maximum cycle numbers, which has provided an extra strength to the proposed and existing methods. The experimental results were tested with sets of fifteen numerical benchmark functions. The obtained results from the proposed approach are compared with the several existing approaches such as ABC, GABC and GGABC, result and found to be very profitable. Finally, obtained results are verified with some statistical testing. View Full-Text
Keywords: Global Artificial Bee Colony; Guided Artificial Bee Colony; Bees Meta-Heuristic Global Artificial Bee Colony; Guided Artificial Bee Colony; Bees Meta-Heuristic
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Shah, H.; Tairan, N.; Garg, H.; Ghazali, R. Global Gbest Guided-Artificial Bee Colony Algorithm for Numerical Function Optimization. Computers 2018, 7, 69.

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