Traffic & Transportation Engineering

Cloud Computing- Based Genetic Algorithm to Solve the Shortest Path in Urban Rood Networks

Expand
  • 1.State Key Laboratory of Automobile Simulation and Control,Jilin University,Changchun 130022,Jilin,China;2.Jilin Province Key Laboratory of Road Traffic,Jilin University, Changchun 130022,Jilin,China;3.College of Transportation,Jilin University,Changchun 130022,Jilin,China
杨庆芳(1966-),女,教授,博士生导师,主要从事智能交通运输系统研究.E-mail:yangqf@jlu.edu.cn

Received date: 2013-09-03

  Revised date: 2013-12-22

  Online published: 2014-02-19

Supported by

国家 “863” 计划项目(2012AA112307)

Abstract

Aiming at the heavy calculation load existing in the solution to the shortest path in urban road networks,this paper proposes a parallel genetic algorithm based on MapReduce in light of analysis of the features and short-comings of genetic algorithm,and has validated the effectiveness of this algorithm based on Changchun City's dataof road network features.Experimental results show that the proposed algorithm based on MapReduce is of fasterconvergence rate and shorter running time in comparison with the traditional genetic one; and that the inter- nodecommunication load increases as parallel nodes increase,so that proper selection of node number plays a key role inenhancing the operation efficiency.

Cite this article

Yang Qing- fang Mei Duo Zheng Li- li Ma Ming- hui Wang Wei . Cloud Computing- Based Genetic Algorithm to Solve the Shortest Path in Urban Rood Networks[J]. Journal of South China University of Technology(Natural Science), 2014 , 42(3) : 47 -51,58 . DOI: 10.3969/j.issn.1000-565X.2014.03.008

Outlines

/