Ant Colony Optimization Algorithms: Introduction & its Recent Trends

Authors

  • 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

Keywords:

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

Abstract

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.

References

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  2. Anirudh Shekhawat Pratik Poddar Dinesh Boswa, “Ant colony Optimization Algorithms : Introduction and Beyond”, Indian Institute of Technology Bombay
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  5. Christian Blum, “Ant colony optimization: Introduction and recent trends”, Physics of Life Reviews 2 (2005) 353–373, © 2005 Elsevier B.V. All rights reserved, doi:10.1016/j.plrev.2005.10.00

International Journal of Scientific Research in Science and Technology

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Published

2018-03-25

Issue

Volume 4, Issue 6, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Chaitanya Natani, Shruti Bijawat "Ant Colony Optimization Algorithms: Introduction & its Recent Trends" International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011,Volume 4, Issue 6, pp.73-77, March-April-2018.