Research On Supply Chain Optimization Model Under Fuzzy-random Demand

In recent years, the supply chain management has taken the more important strategic place in the company development, being the third margin source of the company. For many companies that the supply chain management is not their main business, the supply chain management is not only the source of the cost but also the important measure to decrease the cost. However, the purchase cost is the important factor of the whole corporation supply chain, in which the supplier selection is the important part. In the consistent of most goods, the purchase cost consists 70% of the whole cost. Selecting the right supplier and making the proper vendor is the most important part in the whole chain management, which is critical to the corporation cost.Firstly, This article described the research background and reviewed the supplier selection and the distribution of purchasing volume with the relevant research literature, in the end of this article, we have summarized the research and gives a framework for specific research.Secondly,Introduced the fuzzy random variables, as well as the mathematical methods and fuzzy stochastic simulation techniques to solve fuzzy random variables expectation.In the end, we have established a multi-vendor multi- products choosing model in random fuzzy environment to maximize the effectiveness and services; then, fuzzy random variable expectations of mathematical algorithms was introduced to transform the uncertain demand of the outside world into a certain value, thus, the model was transformed into a equivalent certain fuzzy multi-aim form model. Finally in accordance with the multi-objectives optimization method we use lingo to solve the model, using a practical example to compare the mathematical methods and the fuzzy stochastic simulation techniques respectively, with the results obtained, we analysis of the superiority of the fuzzy stochastic simulation techniques.In addition, the main findings and conclusions, and requiring work for further research are summarized at the end of the paper.