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      A practical model for the train-set utilization: The case of Beijing-Tianjin passenger dedicated line in China

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          Abstract

          As a sustainable transportation mode, high-speed railway (HSR) has become an efficient way to meet the huge travel demand. However, due to the high acquisition and maintenance cost, it is impossible to build enough infrastructure and purchase enough train-sets. Great efforts are required to improve the transport capability of HSR. The utilization efficiency of train-sets (carrying tools of HSR) is one of the most important factors of the transport capacity of HSR. In order to enhance the utilization efficiency of the train-sets, this paper proposed a train-set circulation optimization model to minimize the total connection time. An innovative two-stage approach which contains segments generation and segments combination was designed to solve this model. In order to verify the feasibility of the proposed approach, an experiment was carried out in the Beijing-Tianjin passenger dedicated line, to fulfill a 174 trips train diagram. The model results showed that compared with the traditional Ant Colony Algorithm (ACA), the utilization efficiency of train-sets can be increased from 43.4% (ACA) to 46.9% (Two-Stage), and 1 train-set can be saved up to fulfill the same transportation tasks. The approach proposed in the study is faster and more stable than the traditional ones, by using which, the HSR staff can draw up the train-sets circulation plan more quickly and the utilization efficiency of the HSR system is also improved.

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          An overview of recovery models and algorithms for real-time railway rescheduling

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            Allocation of Railway Rolling Stock for Passenger Trains

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              A pragmatic algorithm for the train-set routing: The case of Korea high-speed railway☆

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                10 May 2017
                2017
                : 12
                : 5
                : e0175698
                Affiliations
                [1 ]MOE Key Laboratory for Urban Transportation Complex System Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China
                [2 ]Department of Civil, Environmental, and Infrastructure Engineering, Volgenau School of Engineering, George Mason University, Fairfax, Virginia, United States of America
                Beihang University, CHINA
                Author notes

                Competing Interests: This work received financial support from the “China Railways Corporation”. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                • Conceptualization: YZ LSZ.

                • Data curation: YZ LSZ.

                • Formal analysis: YZ YW.

                • Funding acquisition: YZ LSZ.

                • Investigation: XML ZY.

                • Methodology: YZ LSZ YW.

                • Project administration: YZ LSZ.

                • Resources: YZ YW ZY.

                • Software: YZ LSZ.

                • Supervision: LSZ YW.

                • Validation: YZ LSZ.

                • Visualization: YW.

                • Writing – original draft: YZ LSZ.

                • Writing – review & editing: YZ YW ZY XML.

                ‡ These authors also contributed equally to this work.

                Article
                PONE-D-16-41954
                10.1371/journal.pone.0175698
                5425186
                28489933
                f57a9c93-b291-480e-a93e-2ebd18b32588
                © 2017 Zhou et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 21 October 2016
                : 28 March 2017
                Page count
                Figures: 14, Tables: 4, Pages: 24
                Funding
                Funded by: the Fundamental Research Funds for the Central Universities
                Award ID: 2015YJS094
                Award Recipient :
                This work is financially supported by “China Railways Corporation” (No. 2016X005-D), and “the Fundamental Research Funds for the Central Universities” (2015YJS094). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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