DocumentCode :
2965815
Title :
A hybrid algorithm applied to travelling salesman problem
Author :
Lee, Zne-Jung
Author_Institution :
Dept. of Inf. Manage., Kang-Ning Junior Coll. of Med. Care & Manage., Taiwan
Volume :
1
fYear :
2004
fDate :
21-23 March 2004
Firstpage :
237
Abstract :
In this paper, a hybrid algorithm is proposed for travelling salesman problem (TSP). TSP, one of the vehicle route planning problems, is to minimize the cost of travel of a salesman in visiting all the cities in a given set, and return to the starting city. Basically, the proposed algorithm combines ant colony optimization (ACO) with genetic algorithm (GA) and can explore and exploit search spaces. It has both the advantage of ACO, the ability to find feasible solutions and to avoid premature convergence, and that of GA, the ability to avoid being trapped in local optima. The test results show that proposed algorithm finds optimum solutions effectively.
Keywords :
cost reduction; genetic algorithms; transportation; travelling salesman problems; GA; TSP; ant colony optimization; convergence; cost minimisation; genetic algorithm; traveling salesman problem; vehicle route planning problem; Ant colony optimization; Cities and towns; Costs; Educational institutions; Genetic algorithms; Health information management; Space exploration; Testing; Traveling salesman problems; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networking, Sensing and Control, 2004 IEEE International Conference on
ISSN :
1810-7869
Print_ISBN :
0-7803-8193-9
Type :
conf
DOI :
10.1109/ICNSC.2004.1297441
Filename :
1297441
Link To Document :
بازگشت