DocumentCode
2559883
Title
An improved genetic algorithm for the multiple traveling salesman problem
Author
Zhao, Fanggeng ; Dong, Jinyan ; Li, Sujian ; Yang, Xirui
Author_Institution
Dept. of Vehicle Manage., Vehicle Manage. Inst., Bengbu
fYear
2008
fDate
2-4 July 2008
Firstpage
1935
Lastpage
1939
Abstract
In this paper, an improved genetic algorithm for the multiple traveling salesman problem was proposed. In the algorithm, a pheromone-based crossover operator is designed, and a local search procedure is used to act as the mutation operator. The pheromone-based crossover can utilize both the heuristic information, including edge lengths and adjacency relations, and pheromone to construct offspring. Experimental results for benchmark instances clearly show the superiority of our genetic algorithm.
Keywords
genetic algorithms; travelling salesman problems; genetic algorithm; heuristic information; local search procedure; multiple traveling salesman problem; mutation operator; pheromone-based crossover operator; Genetic algorithms; Traveling salesman problems; Genetic Algorithm; Multiple Traveling Salesman Problem; Pheromone-based Crossover;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location
Yantai, Shandong
Print_ISBN
978-1-4244-1733-9
Electronic_ISBN
978-1-4244-1734-6
Type
conf
DOI
10.1109/CCDC.2008.4597663
Filename
4597663
Link To Document