摘要
为了解决在求解城市路网最短路径时遇到的数据量大的问题,提出了基于云计算的蚁群算法。该算法结合了模拟退火算法,在弥补蚁群算法缺点的同时,与MPI并行蚁群算法相比,随着节点数的增加运行速度明显加快。
In order to solve the problem of large amount of data encountered in solving the shortest path of urban road network, in this paper, an ant colony optimization algorithm based on cloud computing is proposed. The algorithm combines the simulated annealing algorithm, to compensate for the shortcomings of the ant colony algorithm. Compared to Message Passing Interface （MPI） parallel ant colony algorithm, with the increase in the nodes the running speed of the proposed algorithm is accelerated noticeably.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2013年第5期1210-1214,共5页
Journal of Jilin University:Engineering and Technology Edition
基金
'863'国家高技术研究发展计划项目(2012AA112307)
关键词
交通运输系统工程
城市路网
最短路径
云计算
蚁群算法
engineering of communications and transportation system
urban road network
shortestpath
cloud computing
ant colony optimization
