The Study On Optimization Of Online Ordering Service Distribution Scheme Of High-Speed Railway

In recent years,the pace of China's high-speed railway development has been accelerating and the peopled living standards have gradually improved.The demand for better passengers' catering services during the journey has also shown a rapid growth trend.In order to meet the diversified needs of China's high-speed railway passengers,high-speed railway online ordering services came into being.With the continuous increase of online orders of passengers,these problems,such as high delivery failure rate due to the lagging optimization of the distribution plan of the distribution centers of stations,placing orders earlier have appeared and become constraints on China's high-speed railway online ordering.First of all,this paper combs the actual operation modes of China's high-speed railway online ordering service,analyzes the main bodies of the platform operation and the scopes of service and the scopes of business,and summarizes the low accuracy of the existing operation modes and the necessity for passengers to place orders at least an hour in advance and insufficient after-sales services for delivery failure.At the same time,based on the multi-link joint optimization idea in the field of supply chain optimization,the optimization strategy of joint scheduling for production and distribution of high-speed railway online ordering is proposed.Then,China's high-speed railway online ordering foods can be divided into packaged products and ready-to-eat foods.For the package booking business provided by China's high-speed railway online ordering service,a high-speed railway network with the minimum order delivery failure rate as the optimization target,order-scheduled order joint scheduling model is constructed.Due to the complexity of the model solution,a genetic simulated annealing algorithm has designed for the model.At the same time,a joint scheduling model for real-time orders is constructed according to the real-time booking business,and a three-stage heuristic algorithm has designed based on the complexity of model solving.In addition to that,based on the information of actual cooperation merchants,distribution capabilities,historical orders and relative coordinates for Wuhan Station,the offline distribution cases of the package reservation business and the online distribution cases of the real-time ordering business have been constructed.In order to ensure the universality of the model,a randomly generated strategy is adopted for the production capacity and relative coordinates of the merchants.The delivery time window of the order is randomly selected from the actual arrival schedule of Wuhan Station.Finally,according to the solution results of the offline distribution cases of the package,this paper verifies that the pre-storage order joint scheduling model can reduce the failure rate of order delivery to a certain extent and improve the success rate of order delivery.It also verifies the advantages genetic simulated annealing algorithm compared with the genetic algorithm in convergence speed.According to the online distribution cases of food,the joint scheduling model of real-time order can reduce the average service time of orders,and reduce the time of passengers placing orders in advance to some extent.And in the aspect of the efficiency of the algorithm,it proves the three-stage heuristic algorithm has the superiority in solving the real-time order delivery problemsBased on the idea of joint production and distribution scheduling,this paper optimizes the distribution scheme of high-speed railway online ordering service,and designs the optimization models and solving algorithms in a targeted way,which proves the effectiveness of the joint optimization idea.