Ant Colony Optimization Algorithms: Introduction & its Recent Trends

Authors(2) :-Chaitanya Natani, Shruti Bijawat

Ant Colony Optimization (ACO) algorithms be-long to the class of meta-heuristic approach to solve hard combinational optimization problems and were introduced in the 1990’s. The exhilarating source of ant colony optimization is the foraging demeanor of the real ant colonies. This demeanor of ants is exploited in artificial ant colonies for the search of comparative solutions to discrete optimization problems. ACO algorithms were given by DiCaro & M.Dorigo, in the year 1996. This paper is a review of Ant Colony Optimization with its algorithms in horological order with its recent trends.

Authors and Affiliations

Chaitanya Natani
Department of Computer Engineering, Poornima Institute of Engineering & Technology, Jaipur, Rajasthan, India
Shruti Bijawat
Department of Computer Engineering, Poornima Institute of Engineering & Technology, Jaipur, Rajasthan, India

Shortest Path Algorithms, Meta-heuristics, Ant Colony Optimization, Combinatorial Hard Problems

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Publication Details

Published in : Volume 4 | Issue 6 | March-April 2018
Date of Publication : 2018-03-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 73-77
Manuscript Number : IJSRST174617
Publisher : Technoscience Academy

Print ISSN : 2395-6011, Online ISSN : 2395-602X

Cite This Article :

Chaitanya Natani, Shruti Bijawat, " Ant Colony Optimization Algorithms: Introduction & its Recent Trends", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 4, Issue 6, pp.73-77, March-April-2018.
Journal URL : http://ijsrst.com/IJSRST174617

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