Design And Case Study Of Distribution Network In Supply Chain With Postponement Strategy

In nowadays global competitive economy, industrial companies have realized that goods quality increase and service level improvement can only be achieved through a stringent cost control system. Reliable and cost effective distribution plays a very important role in enabling companies to reduce costs and thus gain competitive advantages.In this paper, we first analyze logistics development in China mainland and abroad and introduce key logistics concepts used in following parts such as: distribution, distribution center, supply chain and supply chain management... The analysis of Chinese and foreign literature on distribution network design makes us realize that distribution network design should integrate production, distribution, storage, handling etc... to form a completely optimized supply chain system.Based on multiple logistics functions, the paper introduces the postponement strategies in the network design procedure and makes a mixed integer programming model after an analysis of operation procedure in distribution center, an analysis of impact on distribution system due to implementation of different postponement stratregies, and the definition of the network's cost structure. The objectif of the model is to determine the number and the locations of distribution centers from a list of candidate cities, so as to optimize the logistics flow between the network nodes, and also to determine the implementation node of packaging postponement strategy. A concrete case based on real data is studied.Firstly, we collected and analyzed the distribution data in China mainland from a big international shoes manufacturer. The cost structure of the studied network is adapted to transported products and is based on author personal experience in high quality logistics study and management at a French International Logistics company in China.The genetic algorithm has been adopted to solve the problem because of its multiple advantages in solving this kind of NP problems. A project in C++ has been written to initialize the population and find the optimal solution through selection and reproduction. Initialization of chromosomes and initial population fitness evaluation showed that transport cost represents more than 80% of the total cost, and we realized that by improving the chromosome initialization, the possible solutions in the NP problem could be largely decreased and even to be counted. Finally, we managed to discrete the model through a fine review of cost structure and solution initialization improvements. The program results finally gave us the optimal solution of the problem.