| Logistics timeliness plays a very important role in logistics system.It can directly affect the delivery speed of goods and customer satisfaction,and determine the location and value of goods in the supply chain.How to ensure the timeliness of goods through routing strategy is an important problem that must be solved in the course of enterprise operation.The purpose of this thesis is to study the vehicle routing problem of micro-container transportation based on time window consideration under the LTL Logistics milk-run mode,and put forward the operation model of simultaneous pickup and delivery.This thesis combines the existing three-level logistics sites of municipal,county and township integration and the"micro-box" car-calling mode,carries out sleeping data mining analysis,considers adding time window constraints,and scientifically analyzes and optimizes the vehicle routing problem through mathematical models and algorithm design,so as to ensure the timeliness of goods,improve customer satisfaction and enhance the core value of enterprises.The vehicle routing problem is an NP-hard problem.Based on the idea of divide-andconquer algorithm,this thesis classified and partitions the source of goods.which can not only avoid repeated transportation and waste,but also respond to the goods in time.without waiting for each source to reach a certain number before receiving.At the same time,taking into account the collection and delivery model,which has an important role in improving vehicle loading rate and reducing enterprise costs.With the continuous development of urbanization,the logistics business of many cities has also been rapidly developed.But rural areas lack good infrastructure and services,and logistics costs and delivery time remain high.Adopting the milk-run mode with time window constraints can effectively improve the timeliness of logistics and make the vehicle route shortest.so as to improve the efficiency of logistics collection,reduce the waste of time and cost,and promote the high-quality development of rural logistics industry. |