Global gbest guided-artificial bee colony algorithm for numerical function optimization

Shah, Habib and Tairan, Nasser and Garg, Harish and Ghazali, Rozaida (2018) Global gbest guided-artificial bee colony algorithm for numerical function optimization. Computers, 7 (69). pp. 1-17. ISSN 2073-431X

[img] Text
AJ 2018 (785) Global gbest guided-artificial bee colony algorithm for numerical function optimization.pdf
Restricted to Registered users only

Download (2MB) | Request a copy


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.

Item Type: Article
Uncontrolled Keywords: Global Artificial Bee Colony; Guided Artificial Bee Colony; Bees Meta-Heuristic
Subjects: Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General) > T11.95-12.5 Industrial directories > T58.6-58.62 Management information systems
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: UiTM Student Praktikal
Date Deposited: 07 Dec 2021 06:18
Last Modified: 07 Dec 2021 06:18

Actions (login required)

View Item View Item