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GPU based genetic algorithms for the dynamic sub-area division problem of the transportation system
Shen Z.4; Wang K.4; Wang F.-Y.4; Philp Chen C.L.3
2014
Source PublicationIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume19
Pages5115-5120
AbstractAt the early stage, the transportation system was controlled in a centralized way. As it grows larger, the system becomes decentralized. Nowadays, most of the commercial transportation systems work in a distributed way. The whole city or town is divided into static or dynamic sub-areas by some rules or heuristics. In every sub-area, the strategy is determined independently. As the cloud computing becomes popular, we propose the idea to control and management the transportation in a new centralized way, that is, all the information is collected together at the cloud side. The effect of the centralized control can be no worse than the decentralized one, as the decentralized control strategy is also one strategy of the centralized control. The division of the sub-areas is determined by computational experiments for different scenarios. We adopt the Multi-Agent System (MAS) model for the traffic flow simulation. And we use the Genetic Algorithms (GA) as the method for the computation to obtain good divisions. To overcome the difficult of the heavy computational burdens, we employ the Graphics Processing Unit (GPU) to accelerate the GA. We test the method on a 5×5 lattice road network and the 18 intersection Zhongguancun road network of Beijing. A speedup factor of around 110 is achieved.
URLView the original
Language英語English
Fulltext Access
Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.National University of Defense Technology
2.Chinese Academy of Sciences
3.Universidade de Macau
4.Institute of Automation Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Shen Z.,Wang K.,Wang F.-Y.,et al. GPU based genetic algorithms for the dynamic sub-area division problem of the transportation system[C], 2014, 5115-5120.
APA Shen Z.., Wang K.., Wang F.-Y.., & Philp Chen C.L. (2014). GPU based genetic algorithms for the dynamic sub-area division problem of the transportation system. IFAC Proceedings Volumes (IFAC-PapersOnline), 19, 5115-5120.
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