Application Methods of Ant Colony Algorithm
American Journal of Software Engineering and Applications
Volume 3, Issue 2, April 2014, Pages: 12-20
Received: May 11, 2014; Accepted: Jun. 11, 2014; Published: Jun. 30, 2014
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Elnaz Shafigh Fard, Faculty of Computer Engineering, Najafabad branch, Islamic Azad University, Isfahan, Iran
Khalil Monfaredi, Engineering Faculty, Department of Electrical and Electronic Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran
Mohammad H. Nadimi, Faculty of Computer Engineering, Najafabad branch, Islamic Azad University, Isfahan, Iran
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As one of the most prestigious and beneficial methods of artificial intelligence, ant colony takes the advantage of communal behavior of ants in nature for solving optimization problems in various fields. However, this useful algorithm requires extensive and repetitious computation, as a result, the processing duration of the present algorithm seems to be one of the most serious challenges about it. In order to solve optimization problems in which duration is very important, this paper attempts to review the previously applied methods and consider the advantages and the disadvantages of each method through highlighting the problems algorithm designers encounter.
Ant Colony, Optimization, Process Duration, Artificial Intelligence, Nature
To cite this article
Elnaz Shafigh Fard, Khalil Monfaredi, Mohammad H. Nadimi, Application Methods of Ant Colony Algorithm, American Journal of Software Engineering and Applications. Vol. 3, No. 2, 2014, pp. 12-20. doi: 10.11648/j.ajsea.20140302.11
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