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Erschienen in: Cluster Computing 2/2019

31.03.2018

Carrying capacity and efficiency optimization model for freight train segment train

verfasst von: Pei Wang, Xiaodong Zhang, Boling Han, Maoxiang Lang

Erschienen in: Cluster Computing | Sonderheft 2/2019

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Abstract

With economic expansion having moderated to a “new normal” pace, supply structure of goods and competition state of logistics market has undergone major changes. In order to respond to these changes actively, China Railway Corporation has launched railway express freight block trains to meet with customers’ demands. However, traditional operation conditions require every freight block train fully loaded to make best of transportation capacity. This has caused a series of problems to freight block trains, such as uncertain departure time, unstable running frequency and so on, which cannot meet with the customers’ basic requirements for goods transport and logistics. So it is an urgent task to study the suitable cars’ number and running frequency of railway express freight block trains so as to reduce customers’ costs and increase China Railway Corporation’s profits. Therefore, this paper analyzes the calculation method of customers’ generalized transportation cost and profits of running a railway express freight block train. Then, an optimization model for cars’ number and running frequency of freight block trains is proposed. The objective functions of this model are the minimum general transportation costs of customers and the maximum profits of China Railway Corporation. The model constraints are about transportation capacity, railway freight stations’ operating capacity and so on. Taking railway express freight block trains operated between Beijing and Shanghai as an example, the cars’ number and running frequency are calculated which can effectively reduce customers’ cost and increase China Railway Corporation’s profits. The results can prove the feasibility of the model proposed in this paper.

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Metadaten
Titel
Carrying capacity and efficiency optimization model for freight train segment train
verfasst von
Pei Wang
Xiaodong Zhang
Boling Han
Maoxiang Lang
Publikationsdatum
31.03.2018
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe Sonderheft 2/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-2444-0

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