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A GPU-Based Parallel Genetic Algorithm for Generating Daily Activity Plans

文献类型：期刊论文

作者Wang, Kai1,2; Shen, Zhen2,3
刊名IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
出版日期2012-09-01
卷号13期号:3页码:1474-1480
关键词Artificial societies-Computational experiments-Parallel execution (ACP) artificial transportation system (ATS) compute unified device architecture (CUDA) daily activity plan genetic algorithm (GA) graphics processing unit (GPU) microsimulation
英文摘要As computing technologies develop, there is a trend in traffic simulation research in which the focus is moving from macro- and meso-simulation to micro-simulation since microsimulation can provide more detailed quantitative results. Moreover, the success of the Artificial societies-Computational experiments-Parallel execution (ACP) approach indicates that integrating other metropolitan systems such as logistic, infrastructure, legal and regulatory, and weather and environmental systems to build an Artificial Transportation System (ATS) can be helpful in solving Intelligent Transportation Systems (ITS) problems. However, the computational burden is very heavy as there are many agents interacting in parallel in the ATS. Therefore, a parallel computing tool is desirable. We think that we can employ a Graphics Processing Unit (GPU), which has been applied in many areas. In this paper, we use a GPU-adapted Parallel Genetic Algorithm (PGA) to solve the problem of generating daily activity plans for individual and household agents in the ATS, which is important as the activity plans determine the traffic demand in the ATS. Previous research has shown that GA is effective but that the computational burden is heavy. We extend the work to GPU and test our method on an NVIDIA Tesla C2050 GPU for two scenarios of generating plans for 1000 individual agents and 1000 three-person household agents. Speedup factors of 23 and 32 are obtained compared with implementations on a mainstream CPU.
WOS标题词Science & Technology ; Technology
类目[WOS]Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
研究领域[WOS]Engineering ; Transportation
关键词[WOS]COMPUTATIONAL EXPERIMENTS ; MANAGEMENT ; SYSTEMS ; SIMULATION
收录类别SCI ; SSCI
语种英语
WOS记录号WOS:000312805000044
源URL[http://ir.ia.ac.cn/handle/173211/3652]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
作者单位1.Natl Univ Def Technol, Coll Mechatron Engn & Automat, Ctr Mil Computat Expt & Parallel Syst Technol, Changsha 410073, Hunan Province, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing Engn Res Ctr Intelligent Syst & Technol, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Cloud Comp Ctr, Dongguan Res Inst CASIA, Dongguan 523808, Guangdong, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Kai,Shen, Zhen. A GPU-Based Parallel Genetic Algorithm for Generating Daily Activity Plans[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2012,13(3):1474-1480.
APA Wang, Kai,&Shen, Zhen.(2012).A GPU-Based Parallel Genetic Algorithm for Generating Daily Activity Plans.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,13(3),1474-1480.
MLA Wang, Kai,et al."A GPU-Based Parallel Genetic Algorithm for Generating Daily Activity Plans".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 13.3(2012):1474-1480.

入库方式： OAI收割

来源：自动化研究所

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