Research On Optimization Models And Algorithms In Supply Chain Under Uncertainty

Recently, supply chain management has become an important issue in both research field and practical world. Purchasing, production, distribution are crucial parts of it. Though many researchers have been exploring supply chain and supply chain management, there are many problems to be studied. It is very important to study supply chain management with operational research and other theory, which is a quite pressing task in front of us.This dissertation mainly addresses supplier selection, production planning and distribution decision in supply chain management under the uncertainties. Based on tactics, the corresponding optimization models are developed, and efficient solutions are found, for providing insights for supply chain management.First, this paper analyzes domestic and foreign research status about modeling of supply chain management, points out the uncertainties and their influence in supply chain, and forecasts the uncertain demand with Monte Carlo Method. Demand is assumed to follow normal distribution. Independent random number and correlated random number are respectively generated to simulate independent demand and correlated demand. Great flexibility is achieved owing to the consideration of the demand correlation.Second, considering uncertainties of demand and subjective preference factor, a multi-objective programming model is developed for vendor selection. A combination of AHP with DEA is proposed to determine the integrated weight for the evaluation criteria of vendors. Based on the integrated weight, the multi-objective programming model is converted into a single objective programming model. Illustrations prove the effectiveness of the approach.Third, considering uncertainty and correlation of demand, a multi-objective programming model of production planning is developed for the objectives that profit should be maximized and opportunity loss minimized. Monte Carlo Method and Genetic Algorithms are used to solve the model. The approach is well tested in the experiments, and the solutions are appropriate alternatives for the decision-makers. Finally, considering retailers' different competitive behaviors and the sensitivity of retail quantity to the prices, the order decision of a distribution system is researched. The profit models of manufacture and retailers are developed respectively. Operational research and game theory are utilized to solve the models. The experimental results show that the algorithm can wonderfully analyze the distribution system.