Study On The Optimization Model Of Urban Logistics Delivery Based On Ranking Of Fuzzy Quantities

With the accelerating of urbanization process, the urban logistics has become one of important research areas of modern logistics in China. The well-developed city logistics can help reduce a lot of problems which logistics activities may cause, such as traffic jams and environmental pollution, guarantee the rapid, sustained and healthy development of the urban economy and play an active role in promoting industrial structure adjustment and transformation of cities as a result. In recent years, the economic globalization and the increasing market competition make the development of urban logistics in China demonstrate an intense trend. The policy made by state and government also gives the utmost support to the development of urban logistics distribution. In the revitalization plan of logistics released by China in2009, urban logistics was considered as a priority field for development. However, there exist a number of problems in the industry of urban logistics, such as poor awareness in developing urban logistics, time and region limit for trucks entering the city and confusing patterns of city logistics delivery etc. As a matter of fact, the selection and optimization of urban logistics delivery models have become the most important issue in the contemporary urban logistics delivery.In this paper, based on analyzing the results of urban logistics delivery modes obtained by domestic and foreign scholars, combined with the present situation in China:there are many cities with different sizes and there are enormous differences in the population, logistics and technical level of these cities, we try to improve the existing self-operating distribution mode and present the mode of "An information center, multiple nodes". With this mode, a multi-objective fuzzy linear programming model is esTablish, and then the model is processed and solved by the use of the idea of fuzzy ranking. The purpose is to reduce the waste of resources in the process of logistics for second-tier cities in China. The details are as follows:First, starting with the current situation and problems of China’s urban logistics distribution model, we analyze the existing logistics and delivery modes and compare the differences between regions and cities in China. In view of unreasonable logistics management and confusing modes of logistics and delivery in the third-tier cities, we present the mode:"An information center, multiple nodes" to improve the self-operating delivery model of the original city and its structure, process, scope of application, advantages are concisely interpreted.Second, after a detailed analysis for the impact factors of the city logistics, combined with the actual delivery situation, we employ the fuzzy theory and method to quantify the uncertainty in cost, time, supply and demand. Then we esTablish a multi-objective fuzzy linear programming model with the minimum delivery cost (which is the delivery company’s main concern) and the shortest delivery time (which is the customer’s main concern) as the goals, and the limit of carrying capacity of lorries as constrain conditions. The model is processed and solved by means of ranking indices of fuzzy quantities.Third, taking rice distribution in Jinzhong City in Shanxi Province as an example, we applied the proposed model and verified its applicability. Three concrete ranking indices of fuzzy quantities are chosen to deal with the problem, and the matlab software is utilized to program and solve the model. Finally, the applicability and accuracy of the model are verified by a comparative analysis for the obtained three different results.In short, we present the model "An information center, multiple nodes" to improve the existing self-operating delivery system and clearly describe its structure, process, scope of application and advantages. As far as the method is concerned, we combine the theory of operational research, fuzzy mathematics and logistics to esTablish a multi-objective fuzzy linear programming model and solve the problem by the use of fuzzy ranking methods for the first time so that a reasonable city logistics scheme is obtained.