Robust Supply Chain Network Design And Application Under Uncertain Demand

Supply chain management plays an increasingly important role in the company's response to a rapidly changing economic environment and fierce competitive pressures.Good supply chain management can enable companies to maintain a strong competitive advantage.Supply chain network design is an important link in supply chain management.It is the basis for ensuring the stable operation of the supply chain network.It can make important decisions on the location,quantity,supply chain network transportation path,product output and other important;information,and provide scientific research for production and operation.in accordance with.There are many uncertainties involved in the design of the.supply chain network.These uncertainties make the supply chain network at risk.Due to the influence and threat of these uncertain factors,the supply chain network has the risk of instability or even failure.The robust optimization method can effectively deal with the uncertainty and can be applied to the processing of uncertain parameters in the supply chain network.By constructing the model by robust optimization method,the corresponding robust feasible solutions can be obtained,which provides decision makers with robust supply chain network decision-making schemes.In recent years,more and more scholars have studied robust optimization methods.Based on this,this paper is based on a multi-product,multi-cycle four-level supply chain network.The four-level supply chain network is composed of suppliers,factories,distribution centers and customer areas.The robust supply chain network is studied under the uncertainty of customer demand.Design problem.On the description of uncertain factors,on the one hand,the scenario analysis method is applied,and the elastic-robust method is applied to establish the supply chain network design model.On the other hand,considering that the decision maker has the preset target cost,the uncertainty set method is used to describe the uncertainty of the demand,and the target-oriented robust optimization method is applied to maximize the uncertainty set parameter as the objective function and establish the robust supply.Chain network design model.Finally,the actual case is enumerated and brought into the relevant parameter solving model.The structure shows that the model established in this paper is stable and effective.The main contents of this paper are:(1)Considering the uncertainty of demand,the elastic-robust optimization method is used to construct and solve the supply chain network design model.The situational uncertainty is described by scenario,and the total cost of supply chain is minimized as the objective function.Under the elastic-robust modeling criterion,the supply chain network design model is established,and then the model is solved and analyzed.(2)On the basis of the above research,and the decision of the decision of the above research,and the target of the above research,and the decision of the decision maker has The uncertainty set parameters are introduced,and the uncertainty set is described by the uncertainty set form.The target-oriented robust optimization method is applied to establish a robust supply chain network design model,and a robust supply chain network design scheme is obtained.,the cost and risk of the supply chain network can be balanced by adjusting the target cost presets.(3)Practical application research.In the practical application research,in the context of SA enterprises,SA enterprises are four-level supply chain networks,and the four-level supply chain network is composed of suppliers,factories,distribution centers and customer areas.First,the supplier supplies the raw materials to the factory.The factory produces the raw materials into various types of products,which are then transported to the distribution center,which delivers the products to the market.This paper studies the design of robust supply chain networks with uncertain demand.The model can meet the relevant needs of different decision makers and provide a decision-making scheme that can effectively deal with uncertain disturbances.