DocumentCode :
699086
Title :
TSP Solution Using Dimensional Ant Colony Optimization
Author :
Pragya ; Dutta, Maitreyee ; Pratyush
Author_Institution :
Dept. of CS & Eng., NITTTR, Chandigarh, India
fYear :
2015
fDate :
21-22 Feb. 2015
Firstpage :
506
Lastpage :
512
Abstract :
This paper describes Dimensional Ant Colony Optimization (DACO), a distributed algorithm that will be applied to solve traveling salesman problem (TSP). In an Any Colony System (ACS), a set of co-operating agents called ants co-operate to find the good solutions of TSPs. Ants co-operate using an indirect form of communication that is mediated by pheromone they deposited on the edges of the TSP graph when building solutions. The proposed system (Dimensional ACO) based on basic ACO algorithm with well defined distribution strategy in which entire search space area is initially being divided into N numbers of hyper-cubic quadrants where N is the dimension of entire search space area for updation of heuristic parameter of ACO and to improve the performance while solving TSP. From our experiments, this proposed algorithm has better performance than other standard bench mark algorithms.
Keywords :
ant colony optimisation; distributed algorithms; distribution strategy; graph theory; travelling salesman problems; ACS; DACO; TSP graph; ant colony system; dimensional ant colony optimization; distributed algorithm; distribution strategy; heuristic parameter; hyper-cubic quadrants; search space area; traveling salesman problem; Algorithm design and analysis; Ant colony optimization; Cities and towns; Convergence; Heuristic algorithms; Optimization; Traveling salesman problems; ACO; DACO; TSP; global minima; pheromone;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computing & Communication Technologies (ACCT), 2015 Fifth International Conference on
Conference_Location :
Haryana
Print_ISBN :
978-1-4799-8487-9
Type :
conf
DOI :
10.1109/ACCT.2015.61
Filename :
7079136
Link To Document :
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