| In recent years,with the continuous improvement of the national economy and the acceleration of the pace of life,the competition in the e-commerce industry has become more and more fierce,and people’s consumption concepts have also undergone great changes.Consumers are becoming more and more sensitive to the concept of time,and their needs are becoming more and more personalized and refined.They always expect that the products they buy can be delivered in time to meet their needs.Therefore,in the environment of increasingly fierce market competition,it is very important for logistics enterprises to meet the high punctuality of commodity distribution to improve customer satisfaction.In this regard,enterprises need to formulate a reasonable and effective distribution plan,and at the same time consider the situation that new orders will appear at any time during the distribution process.This paper focuses on the initial static distribution scheme and the dynamic demand distribution scheme,which has important practical significance in our daily life.This paper firstly introduces customer satisfaction,vehicle routing problem with time window and related theoretical knowledge of blockchain technology,and describes the customer satisfaction function through fuzzy time window.Based on the research of scholars at home and abroad,aiming at the online shopping logistics distribution mode with a wide range of services and complex and changeable needs,comprehensively considering the advantages of blockchain technology and the characteristics of online shopping flow,focusing on meeting customers’ needs for timeliness of delivery,the construction based on The static distribution path optimization model in the initial stage of customer satisfaction and the dynamic demand change distribution path optimization model under the blockchain technology.The model takes the maximum customer satisfaction as the objective function,and considers the constraints such as vehicle load capacity,customer demand and delivery time.Replenishment measures effectively reduce the frequency of replenishment to and from the distribution center,save delivery time,and improve customer satisfaction.An example is designed for simulation experiments,and the genetic algorithm is used to solve the problem,so as to test the validity and applicability of the model.It is concluded that the distribution plan formed by the distribution model under static and dynamic demand can handle new orders in time and effectively optimize the online shopping flow.The delivery level has improved the customer satisfaction. |
