Article
Analyzing the theoretical capacity of railway networks with a radial-backbone topology
Author/s | Ortega Riejos, Francisco Alonso
Barrena, Eva Canca Ortiz, José David Laporte, Gilbert |
Department | Universidad de Sevilla. Departamento de Matemática Aplicada I (ETSII) Universidad de Sevilla. Departamento de Organización Industrial y Gestión de Empresas I |
Publication Date | 2016 |
Deposit Date | 2021-01-22 |
Published in |
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Abstract | In this work we propose a mechanism to optimize the capacity of the main corridor within
a railway network with a radial-backbone or X-tree structure. The radial-backbone (or Xtree)
structure is composed of two types of ... In this work we propose a mechanism to optimize the capacity of the main corridor within a railway network with a radial-backbone or X-tree structure. The radial-backbone (or Xtree) structure is composed of two types of lines: the primary lines that travel exclusively on the common backbone (main corridor) and radial lines which, starting from the common backbone, branch out to individual locations. We define possible line configurations as binary strings and propose operators on them for their analysis, yielding an effective algorithm for generating an optimal design and train frequencies. We test our algorithm on real data for the high speed line Madrid-Seville. A frequency plan consistent with the optimal capacity is then proposed in order to eliminate the number of transfers between lines as well as to minimize the network fleet size, determining the minimum number of vehicles needed to serve all travel demand at maximum occupancy. |
Funding agencies | Ministerio de Economía y Competitividad (MINECO). España Junta de Andalucía Canadian Natural Sciences and Engineering Research Council |
Project ID. | MTM2012-37048
P09-TEP-5022 P10-FQM-5849 39682-10 |
Citation | Ortega Riejos, F.A., Barrena, E., Canca Ortiz, J.D. y Laporte, G. (2016). Analyzing the theoretical capacity of railway networks with a radial-backbone topology. Transportation Research Part A: Policy and Practice, 84 (February 2016), 83-92. |
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