DocumentCode :
2841138
Title :
Solving VRP Using Ant Colony Optimization Algorithm
Author :
Tao, Ning ; Chen, Guo ; Tao, Ning
fYear :
2012
fDate :
24-25 July 2012
Firstpage :
15
Lastpage :
18
Abstract :
Provides a novel hybrid ant colony algorithm combining genetic algorithm with implicit parallel function to make up the shortcomings of common ant colony alogrithm in the vehicle routing problem including slow convergence in the early stages. Introducing the encoding and mutation operation can improve the efficiency of solving the optimal distribution path. The comparative analysis of vehicle routing model and the experimental data shows that the novel hybrid algorithm has not only faster converge speed but the ability to obtain the global optimal solution in a relatively short period.
Keywords :
Convergence; Genetic algorithms; Industries; Logistics; Optimization; Routing; Vehicles; ant colony algorithm; covergence speed; genetic algorithm; vehicle routing problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Computing Science (ICIC), 2012 Fifth International Conference on
Conference_Location :
Liverpool, United Kingdom
ISSN :
2160-7443
Print_ISBN :
978-1-4673-1985-0
Type :
conf
DOI :
10.1109/ICIC.2012.52
Filename :
6258059
Link To Document :
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