The Research And Application Of Supply Chain Inventory Control Problems

In recent years，supply chain inventory control is concerned by domestic and overseasrelevant scholars widely, which is one of center contents of the supply chain management.Under the background of global economic integration, the way of competition is changing inthe nature among enterprises, the competition between two enterprises transform into thecompetition between two supply chains. In this competition, single enterprise doesn’t focuson it’s profit maximization, but pursues the enter supply chain profit maximization.For the sake of coordinating the inventory of the supply chain notes and optimizing costand level of customer service collaboratively, multi-echelon inventory control is employed.Firstly, the basic knowledge of inventory control is introduced and the strategies ofcontrolling inventory are analyzed. The research object which is mesh multi-echeloninventory system including multiply suppliers, single manufacturer and multiply distributorsis defined. In order to solving customer demand random and “BENEFITS AGAINST”problem between cost and level of customer service, safety inventory strategy is proposed. Inaddition, with relationship between safety inventory and the level of customer service andinventory cost, safety factor is considered as decision variable and (t, s, S) replenishmentstrategy is chosen, and the inventory control model is built.Secondly, some solving methods of supply inventory models are summarized, commonintelligent algorithm’s advantages, disadvantages and the characteristic of the model areanalyzed, and genetic algorithm is chosen as the model solving method. With slow rate ofconvergence and tending to produce local value, improved self-adaption genetic algorithm isproposed which adaptively improve it’s operators. Improved self-adaptation genetic algorithmand simple genetic algorithm are used to solve the multi-echelon inventory model.Finally, through the analysis of the results of example simulation by using these twogenetic algorithms, the performances of improved self-adaption genetic algorithm areconcluded, which could not only increase rate of convergence but also get away from localvalue, and improve global of solution. In addition, under the condition of using improvedself-adaption genetic algorithm, it explains the range of safety inventory operator affectsinventory cost and level of customer service. In the end, reasonable optimization schemes areprovided for enter supply chain decision maker.