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