Balancing procurement cost reduction and supplier satisfaction with genetic algorithm

As the second largest in the world, the Chinese automobile market has become more and more important for automakers. However, the competition pressure in this market is ever increasing. To keep profitable, the automobile companies must pay special attention to cost control. Since the procurement cost takes most part of the complete vehicle cost, reducing procurement cost was made the first choice for many manufacturers. However, compared with joint ventures set by world automobile giants, Chinese domestic automakers with smaller scales of production are in adverse position when negotiating the procurement prices with the suppliers. They can not effectively influence the procurement prices and in most cases they need the cooperation from supplier to ensure the security of supply chain for automobile parts. Therefore, the supplier satisfaction is of importance to them and need further study. This research studies the Chinese automobile market and focuses on the fast growing domestic automakers. The relationship between them and their suppliers are also investigated. A supplier satisfaction function is designed and a mathematic model to minimize the decrease of the supplier satisfaction is proposed. Genetic algorithm is employed to search the optimum solution for this model. A case study on this model in a Chinese automobile company is also presented.