An Empirical Study on the Comprehensive Optimization Method of a Train Diagram of the China High Speed Railway Express

Abstract

The rapid and stable development of China’s economy has driven the increasing demand for express transportation. Based on network operation, China Railway Corporation of High-speed Railway launched high-speed rail products, which have attracted wide attention from all walks of life. With the application of high-speed express trains, the market structure of express transportation in China will change dramatically, from highways as the main mode of transportation to high-speed railway transportation relying on a high-speed railway network, which will effectively reduce the environmental pollution caused by express transportation and further improve the sustainable development of the economy and the logistics industry. At present, the freight Electric Multiple Units (EMU) has been successfully developed and has entered the final test stage. In the last paper, we have introduced the theory and method of the high-speed rail express train operation plan. In addition, a train diagram is an important foundation of railway transportation organization. In order to ensure the sustainable development of high-speed rail express trains after they are put into use, based on the operation plan of high-speed rail express trains, this paper establishes a comprehensive compilation model of a high-speed rail express train diagram, considering train running time, freight flow distribution scheme, and the operation plan of freight multiple units, and an exact solution algorithm based on the Lagrange relaxation algorithm is designed. The computational results are encouraging and demonstrate the effectiveness of the model and solution method.

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• https://ideas.repec.org/a/gam/jsusta/v11y2019i7p2141-d221533.html,

https://www.mdpi.com/2071-1050/11/7/2141,

https://doaj.org/article/a8987eda317248a2b5307f565b1cff55,

https://academic.microsoft.com/#/detail/2938778664 under the license cc-by

• https://www.mdpi.com/2071-1050/11/7/2141,

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• https://www.mdpi.com/2071-1050/11/7/2141/pdf,

http://dx.doi.org/10.3390/su11072141

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