Research On VRP Based On Dynamic Demand And Customer Satisfaction

With the rapid development of global economy and modern information technology, the high cost of logistics has seriously affected the development of the national economy, and also weakened the market competitiveness of enterprises. In recent years, Logistics distribution accounted for a high proportion of logistics costs which drew the logistics industry’s great attention on the efficiency of logistics management and processes optimization, researchers gradually turned their attention to our lives which were closely related to various types of vehicle routing problem, and now a lot of results have been achieved.The vehicle routing problem (VRP) is a kind of research about how to optimize the route of vehicles, so that the objective function (usually refers to the distribution costs of enterprises) is minimized. At present, studies on VRP mainly concentrate on the dynamic environment, especially on the changing factors about dynamic demands. The vehicle routing problem with dynamic demands covers a wide range of factors, this paper will add an important index that is customer satisfaction based on dynamic demands. This paper mainly studies how to schedule vehicles effectively in dynamic stage, it could reduce the transport costs for enterprises, and maximize customer satisfaction while satisfying customer demands. This is a problem that many enterprises care about.First of all, this paper reviews the related researches on the vehicle routing problem about dynamic demands both domestic and overseas, customer satisfaction and existing algorithms. Then, introduces the related theory about vehicle routing problem under changes on dynamic demands and customer satisfaction. Hypothesis on the emergence of new customers is the dynamic situation during the distribution process, and brings forward trapezoidal fuzzy subjection function which is used to describe the changes of customer satisfaction. The body of the paper constructed a two-stage optimized model (initial and real-time routing optimization stage) of VRP that considers the dynamic demands changing of customer and customer satisfaction. The concept of virtual distribution center was introduced in real-time stage, and the objective functions contain maximizing the customer satisfaction and minimizing the distribution costs (transportation distance, punishment of waiting time). The real-time stage also transmuted multi-objective function model which was trade-off into single objective function model. Finally, according to the model and real-time optimization strategy, the corresponding genetic algorithm is designed; use MATLAB to program, using Solomon R101 examples and a self-designed dynamic customer demand information to verify. Experimental results verify the effectiveness of the model and rationality of the algorithm.