Long-Term Railway Network Planning Using a Multiperiod Network Design Model
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 1
Abstract
Railway networks are one of the major parts of the transportation infrastructure. Development of this network by the construction of new lines or the capacity improvement of existing lines needs time and capital cost. Decision makers, who are responsible for the infrastructure network, always have a limited budget. They need to select the best package from the long list of new projects. Providing an optimal periodic plan for investment in the railway network is a major task for the government. In this paper, a solution for this task is developed by using a multiperiod network design model for the railway network. The formulation of the model and some of the concepts are new. The model considers development projects (new line construction and existing line improvement), available budget in each period, origin–destination demand matrix for each period, block capacity, and technical capacity. The suggested model is implemented for the Iranian railway network and is solved by an exact method that shows efficiency of the model. In addition, based on the nature of demand, different scenarios are considered in the proposed model. The selected projects by the proposed model and their usage percentage show the ability and efficiency of the model.
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Acknowledgments
We sincerely thank Mohammad Karimi, railway engineering graduate, for his assistance. We also sincerely thank Dr. Saeed Mohamadzadeh, Associate Professor of the School of Railway Engineering, who is the President of RAI (Railways of Iran), because of his major support. We thank all of the experts of RAI, who have guided and provided necessary information for the research, especially Vahid Alighardashi, head of Engineering Office, and Iman Ansari, head of Railway Master Planning group.
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©2019 American Society of Civil Engineers.
History
Received: Oct 5, 2018
Accepted: Apr 2, 2019
Published online: Oct 22, 2019
Published in print: Jan 1, 2020
Discussion open until: Mar 22, 2020
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