Title :
An Improved Genetic Algorithm for TSP
Author :
Wang, Li-Ying ; Zhang, Jie ; Li, Hua
Author_Institution :
Shijiazhuang Railway Inst., Shijiazhuang
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;
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
DOI :
10.1109/ICMLC.2007.4370274
