Research On Multi-Echelon Inventory Optimization Of Supplier Chain Management

With the development of Auto field, the competition turns more and more strongly among enterprises. Due to low communication level of many enterprises, the node warehouse under the supplier chain is mainly independent so as to no system consolidation and high stock cost. In order to control cost, reduce stock, many enterprises established distribution centre so as to coordinate and optimize the stock management between upriver and downriver enterprises.Based on Multi-echelon inventory system combined N warehouses of distribution centre. In this paper, it analyses optimization problem of inventory distribution. In order to help enterprise to achieve maximized profits by dispatch among warehouses, the paper not only analyzes and researches the cost of warehouse dispatch, but also considerate OOS time and degree into model. Under the definite resource and ability, confirming user's satisfactory rate, defining stock control policy between distribution centre and warehouses, it minimizes total stock cost, OOS degree and OOS time. According to the request of distribution centre, under environment of supplier chain, combining the characteristics of Multi-echelon inventory in enterprise, by multi-angle analysis, in the paper puts forward multi-target operation model, using characteristic of genetic algorithm optimization to solve the problem by data model so as to achieve optimization distribution way.The paper develops designing and improving again based on original inventory management system. According above model, it not only considerate inventory cost based on original system, but also considerate the cost of OOS time and degree as well. It greatly improves original warehouse dispatch.The aim of paper research is collecting and consolidating the information of node stock and request under supplier chain by establishing above Inventory dispatch model. By getting information, the enterprise optimize Multi-echelon inventory by request so as to reduce the cost. The result of this paper had already used in some Auto parts manufacturing enterprise.