DocumentCode :
499086
Title :
A new method for handling the traveling salesman problem based on parallelized genetic ant colony systems
Author :
Chien, Chih-yao ; Chen, Shyi-Ming
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ. of Sci. & Technol., Taipei, Taiwan
Volume :
5
fYear :
2009
fDate :
12-15 July 2009
Firstpage :
2828
Lastpage :
2833
Abstract :
In this paper, we present a new method for handling the traveling salesman problem, called the parallelized genetic ant colony systems (PGACS). The proposed method combines genetic algorithms with new crossover operations, hybrid mutation operations and ant colony systems with communication strategies. We also make an experiment using three well-known data sets of the traveling salesman problem. The experiment results show that the performance of the proposed method is better than the method presented in in both the result and the convergence time.
Keywords :
genetic algorithms; travelling salesman problems; genetic algorithms; parallelized genetic ant colony systems; traveling salesman problem; Ant colony optimization; Cities and towns; Computer science; Convergence; Cybernetics; Genetic algorithms; Genetic engineering; Machine learning; Simulated annealing; Traveling salesman problems; Ant colony systems; Genetic algorithms; Parallelization; Parallelized genetic ant colony systems; Traveling salesman problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
Type :
conf
DOI :
10.1109/ICMLC.2009.5212601
Filename :
5212601
Link To Document :
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