DocumentCode :
1804281
Title :
An improved ant colony algorithm for vehicle shortest path problem
Author :
Wang, Yue ; Xue, Guoxin ; Long, Shiyu
Author_Institution :
School of Information Science and Engineering, Changzhou University, China
fYear :
2013
fDate :
1-8 Jan. 2013
Firstpage :
1
Lastpage :
3
Abstract :
An algorithm of the transition probability was studied. The model used contains several traffic parameters. Pheromone update strategy including traffic density factor was adopted. the algorithm could resolve the shortest path problem with the real-time trafic information. To avoid local minimal problem, the ant colony algorithm was combined with genetic algorithm. Compared with traditional algorithm, the results of the experimentation showed that the algorithm could find the shortest running path accurately and quickly.
Keywords :
Real-time systems; ant colony algorithm; real-time traffic information; shortest path problem; traffic density;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Conference Anthology, IEEE
Conference_Location :
China
Type :
conf
DOI :
10.1109/ANTHOLOGY.2013.6784917
Filename :
6784917
Link To Document :
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