Open Access
Issue
MATEC Web Conf.
Volume 173, 2018
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation (SMIMA 2018)
Article Number 02002
Number of page(s) 5
Section Automation and Nontraditional Manufacturing
DOI https://doi.org/10.1051/matecconf/201817302002
Published online 19 June 2018
  1. Liu Y F, Zhang A. A collaborative task allocation method for man-machine/UAV formation[J]. Systems Engineering and Electronic Technology, 2010,32(3):484-588. [Google Scholar]
  2. Chen Y. The application of ant colony optimization theory in UAV tactical control[D]. Chang Sha: University of National Defense Science and Technology, 2007. [Google Scholar]
  3. Luo Q. A study on the integrated flight path planning and assignment method of ground attack under multiple threat conditions[D]. Chang Sha: University of National Defense Science and Technology, 2010. [Google Scholar]
  4. Karaboga D. An idea based on honey bee swarm for numerical optimization, Technical Report-tr06 [R]. Engineering Faculty, Erciyes University,2005. [Google Scholar]
  5. Karaboga D.A comparative study of Artificial Bee Colony Algorithm[J]. Applied Mathematics and Computation, 2009,214(1):108-132. [CrossRef] [Google Scholar]
  6. Karaboga, D. On the performance of Artificial Bee Colony(ABC) algorithm[J]. Applied Soft Computing, 2008,8(1):687-697. [CrossRef] [Google Scholar]
  7. Li G Q, Niu P F, Xiao X J. Development and investigation of efficient Artificial Bee Colony algorithm for numerical optimization[J]. Applied Soft Computing, 2012, 12(3): 320-332. [CrossRef] [Google Scholar]
  8. Banharnsakun A, Achalakul T, Sirinaovakul B. The Best so-far selection in Artificial Bee Colony algorithm[J]. Applied Soft Computing, 2011, 11(2): 2888-2901. [CrossRef] [Google Scholar]
  9. Mao S, Xie W J, Zhang J Y, et al. Double evolutional artificial bee colony algorithm for solving vehicle routing problem[J]. Computer Engineering and Applications, 2016, 52(7):35-42. [Google Scholar]
  10. Ozturk C, Hancer E, Karaboga D.A novel binary Artificial Bee Colony algorithm based On genetic operators[J].Information Sciences,2015,297:154-170. [CrossRef] [Google Scholar]
  11. Li Z Y, Wang W Y, Yan Y Y. PS-ABC: A hybrid algorithm based on particle swarm and Artificial Bee Colony for high-dimensional optimization problems[J].Expert Systems With Applications,2015,42(3): 8881-8895. [CrossRef] [Google Scholar]
  12. Wang H, Wu Z J, Rahnamayan S, et al. Multi-strategy ensemble Artificial Bee Colony alg-orithm[J]. Information Sciences, 2014, 279(6): 587-603. [CrossRef] [Google Scholar]
  13. Kefayat M, Lashkar Ara A, Nabavi Niaki S A.A hybrid of ant colony optimization And Artificial Bee Colony algorithm for probabilistic optimal placement and sizing of distributed energy[J].Energy Conversion and Management, 2015(4), 92: 149-161. [CrossRef] [Google Scholar]
  14. Szeto W, Wu Y, Ho S C. An Artificial Bee Colony algorithm for the capacitated vehicle routing problem[J]. European Journal of Operational Research, 2011,215(1):126-135 [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.