Research On Capacity Control For Railway Container Train With Customer Choice Behavior

The railway freight reform considers container transport as an important way to transform to modern logistics enterprises and proposes a series of measures to promote its development.The increase in container freight has become a new bright spot for the growth of railway freight.People pay more and more attention to railway container transport,whose development is restricted by a single accommodation control strategy to some extent.To improve the competitiveness and benefits of the container freight market,more scientific accommodation control methods are needed.The paper studies the capacity control of railway container transportation and takes customer’s choice behavior into account.It embodies the concept of customer-oriented and helps to improve the market competitiveness of railway transportation enterprises.For operational management of transportation,it also provides decision-making reference.The core content of this paper includes the following aspects:First of all,for the container trains that pass through multiple sections,the capacity control strategy that considers different levels of container is studied.Based on the goal of maximizing the revenue of railway transportation enterprises,the paper takes the booking limit of different container levels on each OD as the decision variables and establishes a nonlinear programming model with constraints.When modeling problems,the paper uses nested control methods,which is different from the non-nested control method whose booking limits of each level of product don’t occupy each other.However,the high price level product in the nested control mechanism can occupy the booking limit of the low-price level,so that the booking of the high-grade product can be satisfied to the utmost,thereby increasing income.Then,considering the customer’s upward purchase behavior,the problem of capacity control for direct container trains under the condition of two slot classes was studied.The expected revenue model is established by taking the optimal booking limits of the secondclass container as decision variables.The expression of the optimal booking limits is deduced based on the marginal analysis method.Then the recursive algorithm is designed to calculate the solution of the optimal booking limits.And using an example to analyze the effect of the upward purchasing probability on the optimal booking limits and the expected revenue of the company.Finally,under the conditions of the railway container transportation network,the paper established a dynamic capacity control model that considers the discrete selection behavior of customers.This model can help railway transportation companies make decisions on which transportation products should be opened at the current moment and current state.Because there is a multidimensional difficulty of dynamic programming model directly solving,the dynamic programming model is deterministically transformed and the column generation algorithm is applied to the transformed model.At the same time,according to the duality theory,designing decomposition approximation algorithm directly is in order to seek the approximate solution of the dynamic programming model.The results of the final example show that the company can obtain more benefits with capacity control strategy by considering the customer’s choice behavior than the demand independent.