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Variants of Ant Colony Optimization- A State of an Art


Affiliations
1 Department of Computer Science and Engineering, Bharath University, Chennai - 600073, Tamil Nadu, India
2 Department of Information Technology, Sri Manakula Vinayagar Engineering College, Pondicherry - 605107, India
 

Ant Colony Optimization, a Swarm intelligence method which solves NP hard problems inspired from the behaviour of ant foraging (Searching for food) the heuristics they use and partial guidance by other ants in indirect format (Stigmergy). This paper developed to list out the variations of the ACO application, its variants with clear diagrammatic and graphical representation. Clear denotation of the techniques they have used to solve such problems, representation of problems, transformations, parameters used and advantage of the techniques and used variants. Through this article we identify some open suggestions with a certain interest of being solved in near future.

Keywords

Heuristics, Pheromone, Stigmergy
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  • Variants of Ant Colony Optimization- A State of an Art

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Authors

N. Sakthipriya
Department of Computer Science and Engineering, Bharath University, Chennai - 600073, Tamil Nadu, India
T. Kalaipriyan
Department of Information Technology, Sri Manakula Vinayagar Engineering College, Pondicherry - 605107, India

Abstract


Ant Colony Optimization, a Swarm intelligence method which solves NP hard problems inspired from the behaviour of ant foraging (Searching for food) the heuristics they use and partial guidance by other ants in indirect format (Stigmergy). This paper developed to list out the variations of the ACO application, its variants with clear diagrammatic and graphical representation. Clear denotation of the techniques they have used to solve such problems, representation of problems, transformations, parameters used and advantage of the techniques and used variants. Through this article we identify some open suggestions with a certain interest of being solved in near future.

Keywords


Heuristics, Pheromone, Stigmergy



DOI: https://doi.org/10.17485/ijst%2F2015%2Fv8i31%2F135488