DocumentCode :
691175
Title :
Ant Colony Algorithm and Its Application in Solving the Traveling Salesman Problem
Author :
Shigang Cui ; Shaolong Han
Author_Institution :
Tianjin Key Lab. of Inf. Sensing & Intell. Control, Tianjin Univ. of Technol. & Educ., Tianjin, China
fYear :
2013
fDate :
21-23 Sept. 2013
Firstpage :
1200
Lastpage :
1203
Abstract :
With the modernization of the rapid development of science and technology, high technology has been more and more widely applied. Ant colony algorithm is a novel category of bionic meta-heuristic system and parallel computation and positive feedback mechanism are adopted in this algorithm. Ant colony algorithm, which has strong robustness and is easy to combine with other methods in optimization, has wide application in various combined optimization fields, but the basic ant colony algorithm is of slow convergence and easy to stagnation and easily converges to local solutions. many scholars did a lot of effort to improve these weaknesses, but the research still needs improving. This paper expounds the basic principle, model, advantages and disadvantages of ant colony algorithm and the TSP problem, the concrete realization process of ant colony algorithm is put forward in solving traveling salesman problem and the simulation shows that solution is feasible.
Keywords :
ant colony optimisation; combinatorial mathematics; travelling salesman problems; TSP problem; ant colony algorithm; bionic meta-heuristic system; parallel computation; positive feedback mechanism; traveling salesman problem; Biology; Cities and towns; Convergence; Optimization; Search problems; Software algorithms; Traveling salesman problems; ant colony algorithm; pheromone; the TSP problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Instrumentation, Measurement, Computer, Communication and Control (IMCCC), 2013 Third International Conference on
Conference_Location :
Shenyang
Type :
conf
DOI :
10.1109/IMCCC.2013.266
Filename :
6840656
Link To Document :
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