基于大数据的供应链协同机制研究

Since the development of system structure of supply chain becomes more and more complex, the crossing region becomes wider and wider, the supply chain systems exhibite the typical complexity. The supply chain members have separate, conflicting objectives. Collaborative management of complex supply chain system is the key and the challenge of supply chain management. Under the support of a series of emerging technologies, such as mobile computing, the Internet of things and cloud computing, the production and innovation based on comprehensive information and network model bring the human society into the "third industrial revolution" era. That is, the age of Big Data. The large data of complex supply chain system in the running process has a significant influence on the collaborative management of supply chain. In this case, the collaborative management decision-making of supply chain increasingly depends on data analysis rather than the experience and intuition. Abstracting various useful information from Big Data in real time, optimizing the inventory in real time, optimizating the logistics, and the cooperation of supply chain belong to the emerging new field of supply chain management. This project aims at applying the theories and approaches of Big Data to the research and analysis of supply chain cooperation, the modelling of data flow of the complex supply chain, the analysis of dynamical behaviors,the analysis of collaborative mechanism of supply chain, and the construction of real-time earlier warning system of collaborative supply chain. It has the important theoretical significance and huge social value.

随着供应链系统层次结构变得越来越复杂，所跨地域范围越来越广，供应链系统表现出典型的复杂性特征。供应链成员具有各自独立的、相互冲突的目标，复杂的供应链系统的协同管理是供应链管理的关键和挑战。 在移动计算、物联网、云计算等一系列新兴技术的支持下，全面基于信息和网络的生产和创新模式，将人类社会带入"第三次工业革命"时代，即大数据时代。复杂供应链系统在运行过程中产生的大数据对供应链协同管理有着巨大影响，使得供应链协同管理决策越来越依赖于数据分析而非经验甚至直觉。从大数据中实时获取各种有用信息，进行实时库存优化、物流优化、供应链协同是供应链管理的新的研究领域。 本项目应用大数据理论和方法对供应链协同进行研究和分析，对复杂供应链系统的数据流进行建模并分析其动力学行为，从而分析供应链协同的机理，并建立实时的供应链协同预警系统，是计算机科学、管理科学的交叉研究，具有重要的理论意义和巨大的社会价值。

：随着供应链系统层次结构变得越来越复杂，所跨地域范围越来越广，供应链系 统表现出典型的复杂性特征。供应链成员具有各自独立的、相互冲突的目标，复杂的供应链 系统的协同管理是供应链管理的关键和挑战。 在移动计算、物联网、云计算等一系列新兴技术的支持下，全面基于信息和网络的生产 和创新模式，将人类社会带入“第三次工业革命”时代，即大数据时代。复杂供应链系统在 运行过程中产生的大数据对供应链协同管理有着巨大影响，使得供应链协同管理决策越来越 依赖于数据分析而非经验甚至直觉。从大数据中实时获取各种有用信息，进行实时库存优化、 物流优化、供应链协同是供应链管理的新的研究领域。 本项目应用大数据理论和方法对供应链协同进行研究和分析，对复杂供应链系统的数据 流进行建模并分析其动力学行为，从而分析供应链协同的机理，并建立实时的供应链协同预 警系统，是计算机科学、管理科学的交叉研究，具有重要的理论意义和巨大的社会价值。