DocumentCode
1926201
Title
An Improved Genetic Algorithm for TSP
Author
Wang, Li-Ying ; Zhang, Jie ; Li, Hua
Author_Institution
Shijiazhuang Railway Inst., Shijiazhuang
Volume
2
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
925
Lastpage
928
Abstract
In this paper, an improved Genetic Algorithm is proposed to solve Traveling Salesman Problem (TSP). In order to improve the performance of Genetic Algorithm, untwist operator is introduced. The untwist operator can untie the knots of route effectively, so it can shorten the length of route and quicken the convergent speed. The computation with experimental data shows the untwist operator and the solving method are effective.
Keywords
convergence; genetic algorithms; mathematical operators; transportation; travelling salesman problems; NP-hard combinatorial optimization problem; TSP; convergent speed; genetic algorithm; traveling salesman problem; untwist operator; Biological cells; Cities and towns; Cybernetics; Genetic algorithms; Machine learning; Mathematical model; Mathematics; Physics; Rail transportation; Traveling salesman problems; Genetic algorithm; Traveling salesman problem (TSP); Untwist operator;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-0973-0
Electronic_ISBN
978-1-4244-0973-0
Type
conf
DOI
10.1109/ICMLC.2007.4370274
Filename
4370274
Link To Document