A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session

Bai Li

doi:doi:10.11648/j.acis.20140205.11

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A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session

Bai Li

Published in Automation, Control and Intelligent Systems (Volume 2, Issue 5)

Received: 23 January 2014 Accepted: 4 September 2014 Published: 30 September 2014

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Abstract

The artificial bee colony (ABC) algorithm has been a well-known swarm intelligence algorithm, which assimilates the cooperating behavior of bees when seeking for nectar sources. Aiming to improve the conventional ABC algorithm, we focus on the re-initialization phase. In this paper, an overall-degradation-oriented artificial bee colony (OD-ABC) algorithm is proposed, pursuing to fight against premature convergence. This is achieved through re-initializing majority of the employed bees at one time, rather than generating at most one scout bee in each iteration. In this work, our OD-ABC algorithm is compared against the conventional ABC algorithms using 24 benchmark functions that origin from the CEC 2014’s competition on single objective real-parameter numerical optimization. The numerical results show that the OD-ABC algorithm is effective and thus can be employed to fight against premature convergence.

Published in	Automation, Control and Intelligent Systems (Volume 2, Issue 5)
DOI	10.11648/j.acis.20140205.11
Page(s)	71-80
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Artificial Bee Colony, Numerical Optimization, CEC 2014 Competition, Overall Degradation Strategy, Evolutionary Algorithm

References

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APA Style

Bai Li. (2014). A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session. Automation, Control and Intelligent Systems, 2(5), 71-80. https://doi.org/10.11648/j.acis.20140205.11

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ACS Style

Bai Li. A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session. Autom. Control Intell. Syst. 2014, 2(5), 71-80. doi: 10.11648/j.acis.20140205.11

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AMA Style

Bai Li. A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session. Autom Control Intell Syst. 2014;2(5):71-80. doi: 10.11648/j.acis.20140205.11

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@article{10.11648/j.acis.20140205.11,
  author = {Bai Li},
  title = {A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session},
  journal = {Automation, Control and Intelligent Systems},
  volume = {2},
  number = {5},
  pages = {71-80},
  doi = {10.11648/j.acis.20140205.11},
  url = {https://doi.org/10.11648/j.acis.20140205.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acis.20140205.11},
  abstract = {The artificial bee colony (ABC) algorithm has been a well-known swarm intelligence algorithm, which assimilates the cooperating behavior of bees when seeking for nectar sources. Aiming to improve the conventional ABC algorithm, we focus on the re-initialization phase. In this paper, an overall-degradation-oriented artificial bee colony (OD-ABC) algorithm is proposed, pursuing to fight against premature convergence. This is achieved through re-initializing majority of the employed bees at one time, rather than generating at most one scout bee in each iteration. In this work, our OD-ABC algorithm is compared against the conventional ABC algorithms using 24 benchmark functions that origin from the CEC 2014’s competition on single objective real-parameter numerical optimization. The numerical results show that the OD-ABC algorithm is effective and thus can be employed to fight against premature convergence.},
 year = {2014}
}

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TY  - JOUR
T1  - A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session
AU  - Bai Li
Y1  - 2014/09/30
PY  - 2014
N1  - https://doi.org/10.11648/j.acis.20140205.11
DO  - 10.11648/j.acis.20140205.11
T2  - Automation, Control and Intelligent Systems
JF  - Automation, Control and Intelligent Systems
JO  - Automation, Control and Intelligent Systems
SP  - 71
EP  - 80
PB  - Science Publishing Group
SN  - 2328-5591
UR  - https://doi.org/10.11648/j.acis.20140205.11
AB  - The artificial bee colony (ABC) algorithm has been a well-known swarm intelligence algorithm, which assimilates the cooperating behavior of bees when seeking for nectar sources. Aiming to improve the conventional ABC algorithm, we focus on the re-initialization phase. In this paper, an overall-degradation-oriented artificial bee colony (OD-ABC) algorithm is proposed, pursuing to fight against premature convergence. This is achieved through re-initializing majority of the employed bees at one time, rather than generating at most one scout bee in each iteration. In this work, our OD-ABC algorithm is compared against the conventional ABC algorithms using 24 benchmark functions that origin from the CEC 2014’s competition on single objective real-parameter numerical optimization. The numerical results show that the OD-ABC algorithm is effective and thus can be employed to fight against premature convergence.
VL  - 2
IS  - 5
ER  -

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Author Information

Bai Li

School of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China

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APA Style

Bai Li. (2014). A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session. Automation, Control and Intelligent Systems, 2(5), 71-80. https://doi.org/10.11648/j.acis.20140205.11

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ACS Style

Bai Li. A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session. Autom. Control Intell. Syst. 2014, 2(5), 71-80. doi: 10.11648/j.acis.20140205.11

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AMA Style

Bai Li. A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session. Autom Control Intell Syst. 2014;2(5):71-80. doi: 10.11648/j.acis.20140205.11

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@article{10.11648/j.acis.20140205.11,
  author = {Bai Li},
  title = {A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session},
  journal = {Automation, Control and Intelligent Systems},
  volume = {2},
  number = {5},
  pages = {71-80},
  doi = {10.11648/j.acis.20140205.11},
  url = {https://doi.org/10.11648/j.acis.20140205.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acis.20140205.11},
  abstract = {The artificial bee colony (ABC) algorithm has been a well-known swarm intelligence algorithm, which assimilates the cooperating behavior of bees when seeking for nectar sources. Aiming to improve the conventional ABC algorithm, we focus on the re-initialization phase. In this paper, an overall-degradation-oriented artificial bee colony (OD-ABC) algorithm is proposed, pursuing to fight against premature convergence. This is achieved through re-initializing majority of the employed bees at one time, rather than generating at most one scout bee in each iteration. In this work, our OD-ABC algorithm is compared against the conventional ABC algorithms using 24 benchmark functions that origin from the CEC 2014’s competition on single objective real-parameter numerical optimization. The numerical results show that the OD-ABC algorithm is effective and thus can be employed to fight against premature convergence.},
 year = {2014}
}

Copy | Download

TY  - JOUR
T1  - A Novel Artificial Bee Colony Algorithm with an Overall-Degradation Strategy and Its Performance on the Benchmark Functions of CEC 2014 Special Session
AU  - Bai Li
Y1  - 2014/09/30
PY  - 2014
N1  - https://doi.org/10.11648/j.acis.20140205.11
DO  - 10.11648/j.acis.20140205.11
T2  - Automation, Control and Intelligent Systems
JF  - Automation, Control and Intelligent Systems
JO  - Automation, Control and Intelligent Systems
SP  - 71
EP  - 80
PB  - Science Publishing Group
SN  - 2328-5591
UR  - https://doi.org/10.11648/j.acis.20140205.11
AB  - The artificial bee colony (ABC) algorithm has been a well-known swarm intelligence algorithm, which assimilates the cooperating behavior of bees when seeking for nectar sources. Aiming to improve the conventional ABC algorithm, we focus on the re-initialization phase. In this paper, an overall-degradation-oriented artificial bee colony (OD-ABC) algorithm is proposed, pursuing to fight against premature convergence. This is achieved through re-initializing majority of the employed bees at one time, rather than generating at most one scout bee in each iteration. In this work, our OD-ABC algorithm is compared against the conventional ABC algorithms using 24 benchmark functions that origin from the CEC 2014’s competition on single objective real-parameter numerical optimization. The numerical results show that the OD-ABC algorithm is effective and thus can be employed to fight against premature convergence.
VL  - 2
IS  - 5
ER  -

Copy | Download