Supply Chain Network Design With Risk Mitigation Strategy Under Supply And Demand Uncertainty

The globalization trend of supply chain operation brings multiple uncertainty and risk events to its development.These disturbance factors increase difficulty and complexity of supply chain network design.In order to provide decision-making tools for supply chain management practice of enterprises,this paper studies a multi-level optimization problem under multi-dimensional risk environment by comprehensive using theory of supply chain network design and optimization,uncertainty and method of mixed integer programming,tabu search and other association theories or methods.We study two possible scenarios of this problem which simultaneously takes demand uncertainty and facility disruptions into account,and also integrates several risk mitigation strategies,related specific contents and conclusions are as follows:(1)In this scenario,we study a supply chain network which includes a single supply node,several transshipment points and demand points.There exist both reliable and unreliable transshipment points in the network.Unreliable ones face disruption risks.A robust optimization method is used to handle demand uncertainty and a scenario-based method is used to describe facility disruption and capacity losses.Two types of risk mitigating strategies are integrated into the model.The first is to fortify the unreliable facility with different investment levels.The second is to reserve excess processing capacity in the reliable facility.When disruptions happens emergency transferring occurs between reliable facilities and unreliable ones.We first develop a scenario-based two-stage stochastic programming to optimize expected cost and furthermore a mixed integer linear programming model with p-robust constraints is proposed.Finally,the developed models are validated through randomly generated examples.The result shows that firstly the two proposed risk mitigation strategies can efficiently alleviate disruption risks of unreliable transshipment points,secondly two models can provide relatively conservative and aggressive decision support respectively and thirdly considering risk will cause cost increase and result in redundancy of supply chain structure.(2)In another scenario,we study a network which involves several supply nodes,several transshipment points and demand points and all the supply nodes face disruption risks.Fuzzy theory is used to handle demand uncertainty and a scenario-based method is used to describe supplier disruption and capacity losses.Two proactive strategies include fortification of suppliers and contracting with a primary supplier and a backup supplier are proposed to mitigate disruption risk.A two-stage stochastic programming is developed to optimize expected cost firstly,and then a mathematical optimization model is formulated considering solution robust.Finally a tabu search is designed to solve this problem.And a numerical example is presented to illustrate the model and the feasibility of the proposed algorithm.The result shows that the proposed risk mitigation strategies can efficiently diminish supply disruption risk and the optimizing model(Model?)can effectively reduce the risk level of decision-making for risk averse decision makers.