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Quantum Artificial Bee Colony Algorithm for Numerical Function Optimization

by Nizar Hadi Abbas, Haitham Saadoon Aftan
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 93 - Number 9
Year of Publication: 2014
Authors: Nizar Hadi Abbas, Haitham Saadoon Aftan
10.5120/16244-5800

Nizar Hadi Abbas, Haitham Saadoon Aftan . Quantum Artificial Bee Colony Algorithm for Numerical Function Optimization. International Journal of Computer Applications. 93, 9 ( May 2014), 28-33. DOI=10.5120/16244-5800

@article{ 10.5120/16244-5800,
author = { Nizar Hadi Abbas, Haitham Saadoon Aftan },
title = { Quantum Artificial Bee Colony Algorithm for Numerical Function Optimization },
journal = { International Journal of Computer Applications },
issue_date = { May 2014 },
volume = { 93 },
number = { 9 },
month = { May },
year = { 2014 },
issn = { 0975-8887 },
pages = { 28-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume93/number9/16244-5800/ },
doi = { 10.5120/16244-5800 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:15:22.642726+05:30
%A Nizar Hadi Abbas
%A Haitham Saadoon Aftan
%T Quantum Artificial Bee Colony Algorithm for Numerical Function Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 93
%N 9
%P 28-33
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Artificial Bee Colony (ABC) algorithm is a swarm intelligence based algorithm, which simulate the foraging behavior of honey bee colonies. It has been widely applied to solve the real-world problem. However, ABC has good exploration but poor exploitation abilities, and its convergence speed is also an issue in some cases. In order to overcome these issues, this paper presents a new metaheuristic algorithm called Quantum Artificial Bee Colony (QABC) algorithm for global optimization problems inspired by quantum physics concepts. Simulations are conducted on a suite of unimodal/multimodal continuous benchmark functions. The results demonstrate the good performance of the QABC algorithm in solving complex numerical optimization problems when compared with other popular algorithms.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Artificial bee colony algorithm Swarm intelligence Quantum physics Benchmark functions.

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