Artificial Bee Colony Algorithm Combined with Grenade Explosion Method and Cauchy Operator for Global Optimization
Artificial bee colony (ABC) algorithm is a popular swarm intelligence technique inspired by the intelligent foraging behavior of honey bees. However, ABC is good at exploration but poor at exploitation and its convergence speed is also an issue in some cases. To improve the performance of ABC, a nov...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2015/739437 |
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doaj-4494ef9419964b8c9f00905e2ef7d63c2020-11-24T22:59:32ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472015-01-01201510.1155/2015/739437739437Artificial Bee Colony Algorithm Combined with Grenade Explosion Method and Cauchy Operator for Global OptimizationJian-Guo Zheng0Chao-Qun Zhang1Yong-Quan Zhou2Glorious Sun School of Business and Management, Donghua University, Shanghai 200051, ChinaGlorious Sun School of Business and Management, Donghua University, Shanghai 200051, ChinaCollege of Information Science and Engineering, Guangxi University for Nationalities, Nanning 530006, ChinaArtificial bee colony (ABC) algorithm is a popular swarm intelligence technique inspired by the intelligent foraging behavior of honey bees. However, ABC is good at exploration but poor at exploitation and its convergence speed is also an issue in some cases. To improve the performance of ABC, a novel ABC combined with grenade explosion method (GEM) and Cauchy operator, namely, ABCGC, is proposed. GEM is embedded in the onlooker bees’ phase to enhance the exploitation ability and accelerate convergence of ABCGC; meanwhile, Cauchy operator is introduced into the scout bees’ phase to help ABCGC escape from local optimum and further enhance its exploration ability. Two sets of well-known benchmark functions are used to validate the better performance of ABCGC. The experiments confirm that ABCGC is significantly superior to ABC and other competitors; particularly it converges to the global optimum faster in most cases. These results suggest that ABCGC usually achieves a good balance between exploitation and exploration and can effectively serve as an alternative for global optimization.http://dx.doi.org/10.1155/2015/739437 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jian-Guo Zheng Chao-Qun Zhang Yong-Quan Zhou |
spellingShingle |
Jian-Guo Zheng Chao-Qun Zhang Yong-Quan Zhou Artificial Bee Colony Algorithm Combined with Grenade Explosion Method and Cauchy Operator for Global Optimization Mathematical Problems in Engineering |
author_facet |
Jian-Guo Zheng Chao-Qun Zhang Yong-Quan Zhou |
author_sort |
Jian-Guo Zheng |
title |
Artificial Bee Colony Algorithm Combined with Grenade Explosion Method and Cauchy Operator for Global Optimization |
title_short |
Artificial Bee Colony Algorithm Combined with Grenade Explosion Method and Cauchy Operator for Global Optimization |
title_full |
Artificial Bee Colony Algorithm Combined with Grenade Explosion Method and Cauchy Operator for Global Optimization |
title_fullStr |
Artificial Bee Colony Algorithm Combined with Grenade Explosion Method and Cauchy Operator for Global Optimization |
title_full_unstemmed |
Artificial Bee Colony Algorithm Combined with Grenade Explosion Method and Cauchy Operator for Global Optimization |
title_sort |
artificial bee colony algorithm combined with grenade explosion method and cauchy operator for global optimization |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1024-123X 1563-5147 |
publishDate |
2015-01-01 |
description |
Artificial bee colony (ABC) algorithm is a popular swarm intelligence technique inspired by the intelligent foraging behavior of honey bees. However, ABC is good at exploration but poor at exploitation and its convergence speed is also an issue in some cases. To improve the performance of ABC, a novel ABC combined with grenade explosion method (GEM) and Cauchy operator, namely, ABCGC, is proposed. GEM is embedded in the onlooker bees’ phase to enhance the exploitation ability and accelerate convergence of ABCGC; meanwhile, Cauchy operator is introduced into the scout bees’ phase to help ABCGC escape from local optimum and further enhance its exploration ability. Two sets of well-known benchmark functions are used to validate the better performance of ABCGC. The experiments confirm that ABCGC is significantly superior to ABC and other competitors; particularly it converges to the global optimum faster in most cases. These results suggest that ABCGC usually achieves a good balance between exploitation and exploration and can effectively serve as an alternative for global optimization. |
url |
http://dx.doi.org/10.1155/2015/739437 |
work_keys_str_mv |
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