Robust rolling stock in rapid transit networks

Cadarso, Luís; Marı́n, Ángel

doi:10.1016/j.cor.2010.10.029

Cited by 65 publications

(33 citation statements)

References 13 publications

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“…This is due to the fact that the type of systems we study, i.e., rapid transit systems such as the ones in Cadarso and Marin (2010, 2011, 2012, are generally used once by passengers. This is, it is rare the case where a passenger enters the rapid transit system, changes to another transport system, and again comes back to the rapid transit system to reach his/her destination.…”

Section: Assumptionsmentioning

confidence: 99%

Improved rapid transit network design model: considering transfer effects

Cadarso

Marı́n

2015

Ann Oper Res

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The rail rapid transit network design problem aims at locating train alignments and stations, maximizing demand coverage while competing with the current existing networks. We present a model formulation for computing tight bounds of the linear relaxation of the problem where transfers are also introduced. The number of transfers within a trip is a decisive attribute for attracting passengers: transferring is annoying and undesirable for passengers. We conduct computational experiments on different networks and show how we are able to solve more efficiently problems that have been already solved; sensitivity analysis on several model parameters are also performed so as to demonstrate the robustness of the new formulation.

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Section: Assumptionsmentioning

confidence: 99%

Improved rapid transit network design model: considering transfer effects

Cadarso

Marı́n

2015

Ann Oper Res

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“…They evaluate the solution on three criteria: the service to the passengers, the robustness, and the cost of the circulation. Cadarso and Marin [8] propose a mixed integer optimization model to study suburban rapid transit robust RS assignment. They minimize total costs including service trips, robustness-relevant empty train movements and composition change costs.…”

Section: State Of the Artmentioning

confidence: 99%

“…• The development of an algorithmic framework that allows us to find solutions to the integrated model, which are demonstrated to be superior to the ones obtained with the sequential approach presented in [8,7], • We solve this model using realistic problem instances obtained from the network of the Spanish railway operator RENFE. We also perform sensitivity analysis on model parameters and conduct a multiobjective optimization study.…”

Section: Robust Circulation Of the Rolling Stock Modelmentioning

confidence: 99%

“…The Robust Circulation of the RS Model (RCRSM) is based on the rolling stock assignment and train routing models proposed by Cadarso and Marin [7,8]. They considered the railway rolling stock and train routing problems for rapid transit networks.…”

Section: Robust Circulation Of the Rolling Stock Modelmentioning

confidence: 99%

“…Note that these constraints count the running trains and those ones in depot stations. Depot capacity constraints (8) ensure that the total capacity of the station is not exceeded:…”

Section: Objective Functionmentioning

confidence: 99%

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Improving robustness of rolling stock circulations in rapid transit networks

Cadarso

Marı́n

2014

Computers & Operations Research

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The rolling stock circulation depends on two different problems: the rolling stock assignment and the train routing problems, which up to now have been solved sequentially. We propose a new approach to obtain better and more robust circulations of the rolling stock train units, solving the rolling stock assignment while accounting for the train routing problem. Here robustness means that difficult shunting operations are selectively penalized and propagated delays together with the need for human resources are minimized. This new integrated approach provides a huge model. Then, we solve the integrated model using Benders decomposition, where the main decision is the rolling stock assignment and the train routing is in the second level. For computational reasons we propose a heuristic based on Benders decomposition. Computational experiments show how the current solution operated by RENFE (the main Spanish train operator) can be improved: more robust and efficient solutions are obtained.

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