Simulation Research And Catastrophe Analysis On Large Scale Logistics Organization Based On GIS

In 2019,the volume of e-commerce transactions across the country reached an amazing 34.81 trillion yuan.There is a high-speed surge in the number of logistics orders with the rapid development of e-commerce.During the busiest time in logistics industry,warehouses are out of space everywhere.From an infrastructur point of view,those IOT equipments(RFID,GPS,embedded sensors,etc.)change the methods of how to control logistics system.In the smart environment,logistics nodes are not isolated nodes anymore,but a cohesive logistics network.Each node in the network is related to each other and effects each other.Every logistics node has the risk of cusp catastrophe.The factors of cusp catastrophe are just hidden in the logistics operation datas.This thesis studies the stability of logistics nodes by analyzing these datas.The stability of logistics nodes is usually affected by the internal resource allocation and external logistics pressure,which exactly conforms to the two attributes of the cusp catastrophe theory: state variable and control variable.The cusp catastrophe theory is a powerful tool to study the stability of logistics nodes.Firstly,this thesis introduces the cusp catastrophe model and logistic model which is used to study the stability of logistics nodes.Then,by investigating the logistics industry of J enterprise,we build a three-level logistics simulation platform with the Anylogic software.Based on discrete-event simulation and agent-based simulation,the simulation platform can dynamically simulate the three-level logistics production operation in reality.The design starts from the bottom to top.In the process of building model,we adds personality and psychological model to the employee agents in the logistics nodes.And we collect the real locations of the logistics nodes in reality,so that the simulation fits the actual situation better.After that,we set the parameters reasonably and carry out the simulation on the logistics simulation platform for 30 days.Then we collect the simulation datas and store them.We dedimensionalize the datas,use the processed datas to fit the cusp catastrophe model,optimize the model based on AIC and BIC criteria,and find the qualitative numerical equation of logistics nodes on the quantitative level.With the help of the Cusp surface,we analyze logistics node configuration and risk prevention from the top to bottom,and put forward some reasonable operation suggestions.Finally,we summarize the research results,and make an analysis of the deficiencies in the research.