Research On Comprehensive Optimization Of Automotive Parts Inbound Logistics Based On Transportation And Stock Factors

Currently, China is becoming the largest country of automotive production and consumption in the world gradually. Almost all of the famous automotive makers have established manufacturing plant in China. At the same time, national automotive makers also seek for chances and promote their own competitive power to retain the market share in the sharp competition. In this market environment, superior quality and lower price than congener production are always two mainstays in market competition. As the 3rd profit source, logistics management should be the focus all of makers concerned, inbound logistics is the most hard and complex part, it is necessary to research for it intensively.In inbound logistics, stock and transportation are the most important two parts, their cost occupy a majority of total cost, so that it could play a vital role to optimize them for decreasing the cost in the whole supply chain. At present, stock and transportation are often regarded as two separate parts and research them, however, it is being a paradox phenomenon between then. How to balance the conflict is becoming a crucial problem in the research on inbound logistics system optimization. It will influence the efficiency and cost of inbound logistics system seriously, so it has important practical meaning to study for them deeply.This paper will study on inbound logistics system of automotive part, focus on optimizing stock and transportation links as a whole system, and target will be the best general cost. On the first step, this paper will analyze the present situation of automotive supply chain, including logistics and inventory management, indicated the disadvantages, submitted CPFR management model to promote the efficiency in communicating between suppliers and makers. The risk will be shared by them. Later, it will plan a new supplier selection and evaluation system. For adapt to makers’practical demand, it added to urgent reaction time, the rate of delivery in time, and establish corresponding math model, answer it by improved Genetic Algorithm, and this paper will be verified the feasibility of this model by a practical example. Basis on selecting a suitable supplier, the stock and transportation system will be optimized generally. Allowing for lean production system the most automotive makers adopted and "zero stock" target, this paper is based on the lowest stock cost, establish a stock and transportation bi-level programming model, and refer to ordering frequency, quantities, transportation way ect. For the uncertainty and hard-convergence of bi-level programming model, will design an adaptive Genetic Algorithm to answer it. Finally, the effect of optimization will be verified significantly by a practical example. It can balance the paradox phenomenon effectively, suppliers and makers feel satisfied.