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Swarm Intelligence and Flocking Behavior

Published on August 2015 by Himani, Ashish Girdhar
journal_cover_thumbnail

International Conference on Advancements in Engineering and Technology
Foundation of Computer Science USA
ICAET2015 - Number 10
August 2015
Authors: Himani, Ashish Girdhar
805605e2-039d-4bb0-9839-91bad0557a2d

Himani, Ashish Girdhar . Swarm Intelligence and Flocking Behavior. International Conference on Advancements in Engineering and Technology. ICAET2015, 10 (August 2015), 9-12.

@article{
author = { Himani, Ashish Girdhar },
title = { Swarm Intelligence and Flocking Behavior },
journal = { International Conference on Advancements in Engineering and Technology },
issue_date = { August 2015 },
volume = { ICAET2015 },
number = { 10 },
month = { August },
year = { 2015 },
issn = 0975-8887,
pages = { 9-12 },
numpages = 4,
url = { /proceedings/icaet2015/number10/22276-4146/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advancements in Engineering and Technology
%A Himani
%A Ashish Girdhar
%T Swarm Intelligence and Flocking Behavior
%J International Conference on Advancements in Engineering and Technology
%@ 0975-8887
%V ICAET2015
%N 10
%P 9-12
%D 2015
%I International Journal of Computer Applications
Abstract

Swarm behavior suggests simple methodologies used by agents of swarm to solve complex problems, which using the other optimsation algorithms such as Genetic Algorithms may not be possible to solve. The basic reason behind this is the group behavior in these algorithms. The distributed control mechanism and simple interactive rules can manage the swarm efficiently and effectively. Flocking behavior does not involve central coordination. This paper aims at the review of the Swarm Intelligence algorithms developed so far and its association with flocking model.

References
  1. Beni, G. , Wang, J. , 1993. Swarm Intelligence in Cellular Robotic Systems, Robots and Biological Systems: Towards a New Bionics Springer, Berlin Heidelberg.
  2. Bonabeau,E. ,Dorigo,M. ,Theraulaz,G. ,1999. Swarm intelligence: from natural to artificial systems.
  3. Millonas, M. M. (1994). Swarms, phase transitions, and collective intelligence. In C. G. Langton, Ed. , Artificial Life III. Addison Wesley.
  4. Colorni, A. ,Dorigo, M. ,Maniezzo,V. ,1991. Distributed optimization by ant colonies. In: Proceedings of the first European Conference on Artificial Life.
  5. Karaboga, D. , 2005. An idea based on honey bee swarm for numerical optimization.
  6. Eberhart, R. , Kennedy, J. , 1995. A new optimizer using particle swarm theory (MHS'95). In: Proceedings of the Sixth IEEE International Symposium on Micro Machine and Human Science.
  7. Yang,X. -S. ,Deb,S. ,2009. Cuckoo search via Lévy flights. (NaBIC2009). In: IEEE World Congress on Nature and Biologically Inspired Computing.
  8. Mucherino, A. , Seref, O. , 2007. Monkey Search: A Novel Metaheuristic Search for Global Optimization, Data Mining, Systems Analysis and Optimization in Biomedicine. American Institute of Physics, New York.
  9. Havens, T. C. , Spain, C. J. , Salmon, N. G. , Keller, J. M. , 2008. Roach infestation optimization. In: Proceedings of the IEEE Swarm Intelligence Symposium.
  10. Garcia, F. J. M. , Perez, J. A. M. , 2008. Jumping frogs optimization: a new swarm method for discrete optimization.
  11. http://en. wikipedia. org/wiki/Flocking_(behavior)
  12. Walter J. Gutjahr,2006. Mathematical runtime analysis of ACO algorithms: survey on an emerging issue
  13. Ali Kaveh, Advances in Metaheuristic Algorithms for Optimal Design of Structures.
  14. Shuzhu Zhang, C. K. M. Lee, 2014. Swarm intelligence applied in green logistics: A literature review.
Index Terms

Computer Science
Information Sciences

Keywords

Swarm Intelligence Agents Aco Abc Flocking Pso.