Study On Modeling And Optimizing Of Supply Chain Multi-time Periods Integrated Plan Under Uncertain Environment

The competition among enterprises depends largely on their supply chains in the complicated and changeable social and economic environments. The supply chain includes various uncertainties. Various uncertain factors could affect the supply chain structure and corresponding operations in dynamic economic environment. Therefore, study on modeling and optimizing of supply chain multi-time periods integrated plan under uncertain environment has important theoretical significance and application value.This paper considers various uncertainty factors, and studys multi-time periods supply chain integrated plan under the uncertain environment. The research content as follow:Firstly, considering the constrain of uncertain customers’ demands in different time periods, I studied two cases respectively, including certain production capacity and uncertain production capacity of manufacture. According to the characteristics of this problem, a supply chain multi-time periods integrated plan stochastic programming model with the objective of minizing costs is established and Genetic algorithm is designed to solve this problem.The results of two numeric examples show that uncertain production capacity of manufacture can increase total cost of supply chain.Secondly, considering constrains of uncertain customers’demands and uncertain production capacity of manufacture in different time periods, I studied two cases respectively, with the purchasing lead time or not. According to the characteristics of this problem, a supply chain multi-time period integrated plan stochastic programming model with the objective of minizing costs is established and Genetic algorithm is used to solve it. The result of a numeric example shows that purchasing lead time can increase total cost of supply chain. Finally, considering constrains of uncertain customers’demands and uncertain production capacity of manufacture in different time periods, I studied different stock supply strategies. A supply chain multi-time periods integrated plan stochastic programming model with objective of minizing costs is established and Genetic algorithm is used to solve it. The result of a numeric example shows that appropriate stock supply strategy can reduce inventory cost and total cost of supply chain.