Modeling And Optimization Of Supply Chain Uncertainty Based On Computation Experiment

At each level of the supply chain,there exists the uncertainty which is one of the main reasons caused management difficult.The uncertainty in supply chain is very difficult problem for businesses and organizations in the management and decision-making,but can not be avoided.Therefore,uncertain supply chain management is important for implementing supply chain management pattern and enhancing the international competition power of our country's manufacturing industry.Based on importance of the problem,this paper studies the supply chain to focus on how to manage and control the uncertainty of supply chain issues,to lucubrate the mechanism of uncertainty and its optimization strategies systematically.In a long time,the research of uncertainty in supply chain was mainly restricted to the general system,analyzed the system mainly on restore ways,so it is difficult to avoid some disadvantages.To break this limitation,we need to get rid of stereotypes, use the computational experiment in the uncertainty of supply chain research.Based on the relevant research experience and results at home and abroad,this paper researched the concept of uncertainty,studied the mechanism of uncertainty produced systematically,the source of uncertainty and the factors which increased uncertainty, built the conceptual model which can analyze the mechanism of uncertainty in supply chain.According to the upper study,the paper analyzed the characteristics of complex adaptive system in supply chain,so took supply chain as a pure complex adaptive system.The paper explored the idea of researching uncertainty in the supply chain by computational experiment method that is feasible and studied the principles when modeling followed.Applied computational experiment,took the bottom-up modeling method and used multi-agent modeling(ABM) to build a supply chain simulation platform.On this platform,the paper constructed the model and analyzed the uncertainty of supply chain from the perspective in complex system and studied how the supply,demand,lead time uncertainty impact the overall performance of the supply chain and the operational mechanism.Finally,for the characteristics of uncertainty in supply chain,on the basis of comprehensive analysis above,lucubrated the measures and optimize strategies to reduce the uncertainty in supply chain systematically.This paper proved the method of computational experiment feasible and preponderant by applying it into the supply chain to analyze the characteristics of this system.The paper applied the approach of multi-agent modeling(ABM) to build a supply chain simulation platform,excogitated how such factors as the demand uncertainty,supply uncertainty and lead time uncertainty impact the supply chain overall performance and concluded that the greater uncertainty in supply chain,the poorer the overall performance.After well-known the mechanism of uncertainty,the paper proposed some measures and strategies to reduce the uncertainty of supply chain,which in order to offer reference and guidance for enterprises to reduce the uncertainty of management.