The Research On Vehicle Routing Problem Combined With Crowdsourcing Under Dynamic Demand

In recent years,with the economic growth,online retailing has achieved rapid development.More and more enterprises have solved the technical problem of delivering packages in one day,which greatly improves the consumer’s purchase experience.However,in order to further improve the satisfaction rate of orders and improve the level of service to consumers,logistics distribution is still facing many challenges.Therefore,the last kilometer distribution problem should be highly valued by enterprises.In order to shorten the lead time of the last one kilometer distribution and improve the coverage of one-day express delivery,logistics enterprises are facing tremendous pressure.Some enterprises begin to consider using excess social forces to assist in the distribution tasks,resulting in the appearance of the concept of crowdsourcing distribution.This thesis mainly studies on the basis of the classic vehicle routing problem,combined with the idea of crowdsourcing,making full use of social idle resources to help complete the distribution task,in order to reduce the cost of logistics distribution and the route of distribution.The paper takes full consideration of four main factors,including crowdsourcing,dynamic programming,time window and capacity constraint,then establishes a mathematical model and designs a tabu search algorithm to solve it.The uncertainty parameters involved in the crowdsourcing,such as the number of vehicles,the capacity of the vehicles,the service scope of the vehicles and the degree of compensation for the drivers are analyzed to find the optimal model of the crowdsourcing distribution.Then this paper compares the model with the traditional VRP model,which proves that the model of the crowdsourcing distribution does save the total distribution cost and the length of the total distribution path.In order to conduct further study,this paper also explores crowdsourcing mode when the number of distribution centers is different.It will provide a reference for future research on crowdsourcing logistics distribution.