scholarly journals A three-step Benders decomposition for the real-time Railway Traffic Management Problem

2020 ◽  
Vol 13 ◽  
pp. 100170
Author(s):  
Kaba Keita ◽  
Paola Pellegrini ◽  
Joaquin Rodriguez
2015 ◽  
Vol 10 ◽  
pp. 534-543 ◽  
Author(s):  
Marcella Sama‘ ◽  
Paola Pellegrini ◽  
Andrea D’Ariano ◽  
Joaquin Rodriguez ◽  
Dario Pacciarelli

2021 ◽  
Vol 54 (2) ◽  
pp. 187-194
Author(s):  
Grégory Marlière ◽  
Sonia Sobieraj Richard ◽  
Paola Pellegrini ◽  
Joaquin Rodriguez

2015 ◽  
Vol 16 (5) ◽  
pp. 2609-2619 ◽  
Author(s):  
Paola Pellegrini ◽  
Gregory Marliere ◽  
Raffaele Pesenti ◽  
Joaquin Rodriguez

Author(s):  
István Ferenc Lövétei ◽  
Bálint Kővári ◽  
Tamás Bécsi

Solving a real-time Railway Traffic Management Problem (rtRTMP) is a challenging task for human operators. To solve the traffic situation, many factors need to be considered. Traditionally, the most critical factor is the availability of the possible routes and the relative position of the vehicles to each other. Besides, additional constraints can be found, such as the velocity, the length, and railway company regulations. The human decision-making process is essential in case of any disturbance (deviation from the pre-planned timetable). The human operator may solve this situation, but generally, the solution is not optimal. In this paper, the authors present a new method, where they consider an MCTS based algorithm to solve the traffic situation in a fast way in a given station. The performance of the algorithm is examined in two abstraction levels. The main purpose is to execute an experimental study to examine the efficiency of the MCTS based algorithms to solve railway traffic situations.


2018 ◽  
Vol 51 (9) ◽  
pp. 106-111 ◽  
Author(s):  
Xiaojie Luan ◽  
Bart De Schutter ◽  
Ton van den Boom ◽  
Francesco Corman ◽  
Gabriel Lodewijks

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