Research On Joint Distribution Routing Optimization With Priority

Chinese logistics industry is developing in the direction of digitization and intelligence,and collaborative sharing to promote resource integration is one of the inevitable trends in the development of smart logistics.Jointly building an intelligent platform and sharing resource information is the focus of the digital transformation of the logistics industry.With the accelerated pace of urban life and the aging of the population,people pay more and more attention to the convenience of life,and the scale of online retail continues to grow.The outbreak of the epidemic in 2020 has accelerated the shift of consumption to online.Facing the surge of orders and more and more diverse customer demands,how to maximize the distribution profits of enterprises while ensuring service quality is a problem faced by enterprises.Codistribution is an inevitable trend of intelligent logistics development,but also an effective way to solve the above-mentioned problems.Therefore,this paper studies the route optimization model considering customer distribution priority.Firstly,analyze the current development status and trend of the logistics industry,clarify the research significance of the paper,sort out the research status at home and abroad,determine the main content framework of the paper,introduce the relevant theories of common distribution path optimization,and provide a theoretical basis for the following.Secondly,considering that it is impossible to meet the service requirements of multiple customers at the same time in the delivery process,analyze the factors that affect the customer’s delivery priority,use the geometric weighting method to calculate the customer’s delivery priority,and propose the time penalty cost for distinguishing different customers by delivery priority.The delivery priority coefficient is added to the time penalty cost,so that the late penalty cost is no longer fixed.Different priorities correspond to different penalty costs.With the goal of minimizing the total delivery cost,two path optimization models are constructed to consider priority.A multi-vehicle path optimization model with advanced levels and a singlevehicle path optimization model considering priorities.Then use the improved AP clustering algorithm to perform cluster analysis on all customers according to the receiving location and delivery time range,assign customers to different delivery clusters,and then use the genetic algorithm to solve the problem,improve the algorithm solution efficiency.Finally,Matlab programming is used to realize the algorithm,combining with the numerical example data,to solve the common distribution mode of single vehicle considering priority and multi-vehicle considering priority.Comparing and analyzing the distribution schemes,the results show that the common distribution mode has obvious advantages in reducing logistics costs,reducing the number of vehicles used,and improving the utilization rate of vehicles.In addition,it is found that the single-model co-delivery plan that considers the delivery priority has the shortest total lateness time and the highest customer satisfaction,but this is based on sacrificing other interests,and the cost to be paid is relatively large,which is not proportional to the value it brings.It is not very desirable.The multi-model co-distribution scheme that considers the priority of delivery has the best comprehensive effect.It can not only improve vehicle utilization,reduce fuel consumption costs,comply with national energy conservation and emission reduction policies,but also reduce logistics costs and improve customer satisfaction.It is of great reference significance to locate logistics enterprises with high-quality services,which is conducive to maintaining long-term interests and improving comprehensive benefits.