Research On Dynamic Pricing Of Railway Freight Driven By Highway Market Freight Rate

In China’s freight transportation market,railway freight transportation has always occupied an important position because of its strong transportation capacity,excellent safety,low freight rate and suitability for long-distance transportation.In recent years,with the continuous maturity of China’s cargo transportation market and the rapid rise of road transportation,the competition in the transportation market has gradually intensified,which has brought great challenges to the railway freight operation.Formulating a reasonable pricing strategy for railway freight transportation is a key factor to improve the economic benefits of railway freight transportation.However,cost-based pricing,which is currently used in China’s railways,can’t fully adapt to the highly competitive transportation market,which will not only have a negative impact on the benefits of railway freight enterprises,but also inhibit the advantages of railway freight in the market competition.Therefore,in view of the lack of market competitiveness of railway freight,it is very important for railway freight enterprises to explore the pricing strategy of railway freight in the competitive environment of public railways and formulate a scientific pricing system.Therefore,this paper takes the dynamic pricing of railway freight driven by highway freight rate as the research direction,and the main contents are as follows:First of all,monitor the road freight transport market,analyze the changing trend of road freight rate with macro-economy,market supply and demand,transportation cost and other factors,build a road freight market freight rate prediction model based on deep learning,and capture the influence of market factors on road freight market freight rate,so as to predict road freight rate.Secondly,it is proposed to take the maximum total profit of railway freight enterprises as the upper goal and the minimum generalized transportation cost of customers as the lower goal.On the basis of fully analyzing the constraints of road network transportation capacity and transportation cost,highway freight rate level and customers’ choice of transportation mode,a bilevel programming model for dynamic pricing of railway freight is established,and a hybrid particle swarm genetic algorithm is designed to solve the bilevel programming model.Finally,taking the simple road network of S Railway Bureau as an example,the relevant data are selected and calculated,and the freight sharing amount and the optimal freight rate among OD in the road network are obtained to verify the feasibility of the model and algorithm.The purpose of this paper is to make the railway freight pricing strategy more competitive and more suitable for the market demand,make the railway transport enterprises gain more benefits in the competition through pricing optimization,and at the same time reduce the generalized transport costs of customers as much as possible,so as to realize the long-term stable development situation of win-win for railway freight transport enterprises and customers.This research is of great significance for railway freight enterprises to improve the price decision-making system,enhance the competitiveness of railway freight market and reduce the social logistics cost.