摘要
近年来,大数据、云计算与物联网为复杂系统的组织与管理提供了有力的新型信息化技术,并引起了企业的组织架构与运营机制的多方面变化.基于此,本文首先针对大数据驱动的大型自行车共享系统构建了一个新的随机模型,既表达了大数据的重要作用,又描述了大型自行车共享系统的运营过程,特别是使用卡车对各个站点自行车的再平衡.其次,本文提出了一种研究大数据驱动的大型自行车共享系统的平均场极限理论,包括利用平均场理论建立非时齐的排队系统,由非时齐的排队系统建立系统的平均场方程组;给出了经验测度过程(empirical measure process)的非线性生灭过程,提出了分段结构下生灭过程的固定点的有效算法,由此能够计算每个站点稳态平均自行车数;用数值算例分析了每个站点稳态平均自行车数是如何依赖于自行车共享系统中的一些关键参数的.基于此,本文对大数据在大型自行车共享系统中所引起的物理效应进行了建模分析,从而为大型自行车共享系统的随机分析提供了一个极有研究潜力的重要发展方向.
Recently, big data, could computing and internet of things provide some new information technologies for organization and management of complex systems, and they have caused multifaceted changes on organization framework and operations mechanism of enterprises. Based on this, we first construct a new stochastic model for a big d ata driven large-scale bike-sharing system, which expresses the important role played by big data, and describes the operations mechanism of the large-scale bike-sharing system, and specifically, the rebalancing of bikes in various stations in terms of trucks. Then, we present a mean-field limit theory, which is applied to analyzing the big d a ta driven large-scale bike-sharing system, including establishing a time-inhomogeneous queueing system by means of the mean field theory, and setting up the meanfield equations through the time-inhomogeneous queueing system; providing an empirical measure process by means of a nonlinear birth-death process, giving algorithms for computing the fixed point in terms of a segmented structural birth-death processes, and computing the average number of bikes in each station; and providing numerical examples to analyze how the steady average number of bikes in each station depends on some key parameters of the bike-sharing system. Using these results, this paper analyzes physical effect of big data on performance of the large-scale bike-sharing. Therefore, this paper gives a promising research direction of stochastic model in the study of large-scale bike-sharing systems.
出处
《应用概率统计》
CSCD
北大核心
2016年第5期499-518,共20页
Chinese Journal of Applied Probability and Statistics
基金
国家自然科学基金项目(71271187
71471160
71471114)
河北省自然科学基金项目(A2012203125)
河北省高等学校创新团队领军人才培育计划(LJRC027)联合资助
