Research On Vehicles' Routing Problem Of Furniture Logistics Facing Uncertainty Traffic

With the rapid development of market economy, as "the third-party source of profit", logistics have become an increasing concern by people. Distribution is a logistics activity that is the entire logistics system terminal, directly facing the customers. The efficiency of distribution, its cost and quality will affect the overall effectiveness of the logistics activities and the customer satisfaction to enterprise logistics service. The vehicle routing problem (VRP) has significant influence on distribution costs and timeliness. Considering there are different road conditions, the distribution vehicle routing optimization results tend to cause some changes, such as avoiding the poor quality of road, congestion part of the route, and so on, even if these sections is probably the most short way. Furniture logistics distribution in sales takes a large cost, and also influences the customer satisfaction, causing furniture sales enterprise of a concern. In this context, the paper mainly does the following:First of all, based on the current domestic and international furniture logistics distribution, this paper puts forward the research background, significance, and reviews VRP models and algorithm. Then,considering the road conditions in certain information conditions, the article establishes the logistics distribution vehicle routing optimization models. On that basis, considering when road in uncertainty information conditions, especially the traffic in random and fuzzy information, the article describes VRP respectively, and establishes VRP model with expectations of the randomness of the information, VRP model with stochastic chance-constrained programming and VRP model with fuzzy information. According to the model, the paper select the improved genetic algorithm and MATLAB software to solve the models. Combined with R furniture company, the article verifies the effectiveness of the model and algorithm. Finally, the article points out the insufficiency parts and the future research direction.