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Artificial Bee Colony Algorithm: A Survey

by Sangeeta Sharma, Pawan Bhambu
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 149 - Number 4
Year of Publication: 2016
Authors: Sangeeta Sharma, Pawan Bhambu
10.5120/ijca2016911384

Sangeeta Sharma, Pawan Bhambu . Artificial Bee Colony Algorithm: A Survey. International Journal of Computer Applications. 149, 4 ( Sep 2016), 11-19. DOI=10.5120/ijca2016911384

@article{ 10.5120/ijca2016911384,
author = { Sangeeta Sharma, Pawan Bhambu },
title = { Artificial Bee Colony Algorithm: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2016 },
volume = { 149 },
number = { 4 },
month = { Sep },
year = { 2016 },
issn = { 0975-8887 },
pages = { 11-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume149/number4/25984-2016911384/ },
doi = { 10.5120/ijca2016911384 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:53:48.334749+05:30
%A Sangeeta Sharma
%A Pawan Bhambu
%T Artificial Bee Colony Algorithm: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 149
%N 4
%P 11-19
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Artificial bee colony optimization algorithm is one of the popular swarm intelligence technique anticipated by D. Karaboga in year 2005. Since its inception, this algorithm was modified by a number of researchers and applied in different areas of engineering, science and management to solve very complex problems. This algorithm is very simple to implement and has the least number of control parameters. In the last two decades, a large number of new algorithm based on natural phenomenon like artificial bee colony algorithm are developed and used to find solution of many real world problems. This paper provides a state of the art survey of ABC algorithm and analysis of its performance with different size of population.

References
  1. D Karaboga, “An Idea based on honey bee swarm for numerical optimization,” Techn. Rep. TR06, Erciyes Univ. Press, Erciyes, 2005.
  2. Brownlee, Clever algorithms: nature-inspired programming recipes. Jason Brownlee, 2011.
  3. D. Karaboga and B. Akay. A comparative study of artificial bee colony algorithm. Applied Mathematics and Computation, 214(1):108–132, 2009.
  4. K. Price, “An Introduction to differential evolution,” New Ideas in Optimization. D. Corne, M. Dorigo, and F. Glover (Eds.), London, UK: McGraw Hill, 1999.
  5. Z Michalewicz and DB Fogel. How to Solve It: Modern Heuristics. Springer, 2004.
  6. JC Bansal, H Sharma and SS Jadon "Artificial bee colony algorithm: a survey." Int. J. of Advanced Intelligence Paradigms 5.1 (2013): 123-159.
  7. Yavuz, Gürcan, and Doğan Aydin. "Angle modulated Artificial Bee Colony algorithms for feature selection." Applied Computational Intelligence and Soft Computing 2016 (2016): 7.
  8. Marinakis, Yannis, Magdalene Marinaki, and Athanasios Migdalas. "A Hybrid Discrete Artificial Bee Colony Algorithm for the Multicast Routing Problem." Applications of Evolutionary Computation. Springer International Publishing, 2016. 203-218.
  9. Sharma, Nirmala, et al. "Modified Artificial Bee Colony Algorithm Based on Disruption Operator." Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Springer Singapore, 2016.
  10. Sharma, Tarun Kumar, and Millie Pant. "Shuffled artificial bee colony algorithm." Soft Computing (2016): 1-20.
  11. Yurtkuran, Alkın, and Erdal Emel. "A discrete artificial bee colony algorithm for single machine scheduling problems." International Journal of Production Research (2016): 1-19.
  12. X. Li and Guangfei Yang. "Artificial bee colony algorithm with memory." Applied Soft Computing (2016).
  13. U. Saif et al. "Hybrid Pareto artificial bee colony algorithm for assembly line balancing with task time variations." International Journal of Computer Integrated Manufacturing (2016): 1-16.
  14. C. Caraveo, Fevrier Valdez, and Oscar Castillo. "Optimization of fuzzy controller design using a new bee colony algorithm with fuzzy dynamic parameter adaptation." Applied Soft Computing 43 (2016): 131-142.
  15. L. Lv et al. "Artificial bee colony algorithm with accelerating convergence." International Journal of Wireless and Mobile Computing 10.1 (2016): 76-82.
  16. S. Kumar, V. K. Sharma, and R. Kumari. "Improved Onlooker Bee Phase in Artificial Bee Colony Algorithm." International Journal of Computer Applications 90.6 (2014): 20-25.
  17. S. Kumar, V. K. Sharma, and R. Kumari, “An Improved Memetic Search in Artificial Bee Colony Algorithm,” International Journal of Computer Science and Information Technology (0975 9646), 5(2): 1237-1247, 2014.
  18. Karaboga, Dervis, and Selcuk Aslan. "A new emigrant creation strategy for parallel artificial bee colony algorithm." 2015 9th International Conference on Electrical and Electronics Engineering (ELECO). IEEE, 2015.
  19. Ozturk, Celal, Emrah Hancer, and Dervis Karaboga. "A novel binary artificial bee colony algorithm based on genetic operators." Information Sciences 297 (2015): 154-170.
  20. S. Kumar, V. K. Sharma, and R. Kumari, “Enhanced Local Search in Artificial Bee Colony Algorithm,” International Journal of Emerging Technologies in Computational and Applied Sciences, 7(2): 177-184, March 2014.
  21. S. Kumar, V. K. Sharma, and R. Kumari, “Randomized Memetic Artificial Bee Colony Algorithm,” International Journal of Emerging Trends and Technologies in Computer Science, 3(1): 52-62, March 2014.
  22. Singhal, Prateek K., et al. "A new strategy based artificial bee colony algorithm for unit commitment problem." Recent Developments in Control, Automation and Power Engineering (RDCAPE), 2015 International Conference on. IEEE, 2015.
  23. S. Kumar, R. Kumari and V. K. Sharma, “A Novel Hybrid Crossover Based Artificial Bee Colony Algorithm for Optimization Problems,” International Journal of Computer Applications (0975 8887) 82(8):18-25, November 2013.
  24. Shailesh Pandey and Sandeep Kumar, “Enhanced Artificial Bee Colony Algorithm and It’s Application to Travelling Salesman Problem,” HCTL Open International Journal of Technology Innovations and Research, Vol 2, March 2013, Pages 137-146, ISSN: 2321-1814, ISBN: 978-1-62776-111-6.
  25. S. Kumar, A. Kumar, V. K. Sharma and H. Sharma, “A Novel Hybrid Memetic Search in Artificial Bee Colony Algorithm,” In Proceedings of IC3 2014 – The Seventh IEEE International Conference on Contemporary Computing. 7 -9 Aug 2014. pp 68 - 73. DOI: 10.1109/IC3.2014.6897149.
  26. Kıran, Mustafa Servet, and Oğuz Fındık. "A directed artificial bee colony algorithm." Applied Soft Computing 26 (2015): 454-462.
  27. S. Kumar, V. K. Sharma, and R. Kumari, “Memetic Search in Artificial Bee Colony Algorithm with Fitness based Position Update,” In Proceedings of IEEE International Conference On Recent Advances and Innovations in Engineering (ICRAIE-2014). 09-11, May 2014. pp 1-6, DOI: 10.1109/ICRAIE.2014.6909301
  28. Mansouri, P., B. Asady, and N. Gupta. "The Bisection–Artificial Bee Colony algorithm to solve Fixed point problems." Applied Soft Computing 26 (2015): 143-148.
  29. J. C. Bansal, H. Sharma, and S. S. Jadon. "Artificial bee colony algorithm: a survey." International Journal of Advanced Intelligence Paradigms 5.1-2 (2013): 123-159.
Index Terms

Computer Science
Information Sciences

Keywords

Nature Inspired Algorithm Memetic algorithm Swarm intelligence Evolutionary computation.

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