Modelling and Simulation of the Supply Chain of Automobile Industry

In this work, a model is built to simulate the dynamic evolution of consumption-driving supply chain system of automobile industry on the geographic information system (GIS) map using agent based model (ABM) and discrete event modeling method. Meanwhile, this model is established by using the ANYLOGIC simulation software and a connection mechanism which can independently choose the upstream or downstream Agent. First, the reliability of the model has been verified by comparing the sale volumes of products and the changes of parameters of each Agent with the realistic supply chain. Second, this model is confirmed to be a typical scale-free network by analyzing the network characteristics of the model employing complex network theory. Last, it is found that the model moves at a chaotic state, which reflects that this model has nonlinear typical characteristics of complex adaptive systems (CASs). Apart from the dynamic evolutionary process of complex networks of automobile supply chain in the macroscopic level, this model also presents the operating process within all Agents in the microcosmic level. Modeling and simulating the supply chain by integrating the synthesizing complex network and the CAS theory provide a new approach for the supply chain management (SCM) and a theoretical basis and empirical reference for the SCM of automobile industry.