DocumentCode :
2510088
Title :
Solving capacitated vehicle routing problem based on improved genetic algorithm
Author :
Jie-sheng, Wang ; Chang, Liu ; Ying, Zhang
Author_Institution :
Sch. of Electron. & Inf. Eng., Liaoning Univ. of Sci. & Technol., Anshan, China
fYear :
2011
fDate :
23-25 May 2011
Firstpage :
60
Lastpage :
64
Abstract :
Aiming at the capacitated vehicle routing problem (CVRP) in the matter stream delivery field, an improved genetic algorithm (GA) based on local mutation operator is adopted. Two layers chromosome coding scheme is designed which can improve initial solutions. This coding method can insure that the sub-routing is effective to satiety the vehicle capacitated constraints. These improved measures have important significance to depress procedural intricacy degree, advance convergence of algorithm velocity and algorithmic local search ability. The simulation experiment results show the improved genetic algorithm compared with BGA can achieve better optimization results and has better efficiency to solve CVRP.
Keywords :
genetic algorithms; logistics; road traffic; CVRP; advance convergence; algorithm velocity; algorithmic local search ability; capacitated vehicle routing problem; chromosome coding scheme; genetic algorithm; local mutation operator; matter stream delivery field; vehicle capacitated constraints; Biological cells; Encoding; Genetic algorithms; Genetics; Routing; Search problems; Vehicles; Capability Vehicle Routing Problem; Genetic Algorithm; Local Mutation; Two Layers Chromosome;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
Type :
conf
DOI :
10.1109/CCDC.2011.5968146
Filename :
5968146
Link To Document :
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