ACO, Its Modification and Variants
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2014 by IJCTT Journal|
|Year of Publication : 2014|
|Authors : Akash Tayal , Prerna Khurana , Priyanka Mittal , Sanjana Chopra|
|DOI : 10.14445/22312803/IJCTT-V9P159|
Akash Tayal , Prerna Khurana , Priyanka Mittal , Sanjana Chopra."ACO, Its Modification and Variants". International Journal of Computer Trends and Technology (IJCTT) V9(6):310-326, March 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Ant colony optimization (ACO) is a P based metaheuristic algorithm which has been proven as a successful technique and applied to a number of combinatorial optimization problems and is also applied to the Traveling salesman problem (TSP). TSP is a well-known NP-complete combinatorial optimization (CO) problem and has an extensive application background. The presented paper proposes an improved version of Ant Colony Optimization (ACO) by modifying its parameters to yield an optimal result. Also this paper shows the experimental results and comparison between the original ACO and Modified ACO. Further this paper proposes two variants of ACO according to their specific application. Various city distributions have also been discussed and compared.
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Ant Colony Optimization (ACO), Artificial Ants (AA), Combinatorial Optimization (CO), Particle Swarm Optimization (PSO), Travelling Salesman Problem (TSP)