DocumentCode :
2251145
Title :
A new method for solving the traveling salesman problem based on the genetic simulated annealing ant colony system with particle swarm optimization techniques
Author :
Chen, Shyi-Ming ; Chien, Chih-yao
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
Volume :
5
fYear :
2010
fDate :
11-14 July 2010
Firstpage :
2477
Lastpage :
2482
Abstract :
In this paper, we present a new method for solving the traveling salesman problem based on the genetic simulated annealing ant colony system with particle swarm optimization techniques. We also make experiments using the 25 data sets obtained from the TSPLIB and compare the experimental results of the proposed method with the existing methods. The experimental results show that both the average solution and the percentage deviation of the found average solution to the best known solution of the proposed method are better than the existing methods.
Keywords :
genetic algorithms; particle swarm optimisation; simulated annealing; travelling salesman problems; ant colony system; genetic simulated annealing; particle swarm optimization; traveling salesman problem; Biological cells; Cities and towns; Genetics; Machine learning; Particle swarm optimization; Simulated annealing; Traveling salesman problems; Ant colony system; Genetic algorithms; Genetic simulated annealing ant colony system with particle swarm optimization techniques; Particle swarm optimization; Simulated annealing; Traveling salesman problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
Type :
conf
DOI :
10.1109/ICMLC.2010.5580809
Filename :
5580809
Link To Document :
بازگشت