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

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	A GPU-Based Parallel Genetic Algorithm for Generating Daily Activity Plans
	Wang, Kai 1,2; Shen, Zhen2,3
发表期刊	IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
	2012-09-01
卷号	13 期号:3 页码:1474-1480
文章类型	Article
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.
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
WOS标题词	Science & Technology ; Technology
关键词[WOS]	COMPUTATIONAL EXPERIMENTS ; MANAGEMENT ; SYSTEMS ; SIMULATION
收录类别	SCI ; SSCi
语种	英语
WOS研究方向	Engineering ; Transportation
WOS类目	Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号	WOS:000312805000044
引用统计	被引频次：38[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/3652
专题	多模态人工智能系统全国重点实验室_平行智能技术与系统团队
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
第一作者单位	中国科学院自动化研究所
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.

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