The Multi-echelon Inventory Systems Management Based On Cost Optimization

The inventory cost is a primary component of the supply chain cost, and the method for multi-echelon inventory optimization and control must be adopted for the sake of the entire supply chain optimization and control. How to effectively control the multi-echelon inventory system is one of the key factors to improve the operational efficiency of supply chains. Therefore, it has a great meaning to study the problem of inventory cost control in the supply chain management.After summarizing the traditional inventory management methods , this paper integrates the new theory of supply chain management and simulation technology of witness and studies the issue of inventory control based on cost optimization.The first part gives an illustration of research back ground, meaning and main content. The second part has done the further research to the two kinds of supply chain inventory management techniques contains vendor managed inventory and joint managed inventory on the base of single inventory management analysis and inventory conception; And have analyzed their range of application, advantage and disadvantage. The third part mainly introduces the configuration of the multi-echelon inventory systems based on cost. The fourth part discusses a two-echelon distribution inventory system with a central warehouse and multiple retailers, where the retailers face stochastic compound Poisson demand process and random leadtimes. This paper presents an improved approximated method and an average cost per unit time model for the two-echelon inventory distribution system with stochastic demand and random leadtimes is developed. The objective is to minimize the average cost of two-echelon distribution inventory. The fifth part mainly focuses on the issue of modeling and simulating for a two-echelon distribution inventory system in a supply chain environment under uncertain demand through Witness computer simulating technology. Hence model minimization problem is simulating and analyzing by which the optimal ordering critical point are determined. In the end, this dissertation is summarized and further research directions are shown.