The railway planning problem is usually studied from two different points of view: macroscopic and microscopic. We propose a macroscopic approach for the high-speed rail scheduling problem where competitive effects are introduced. We study train frequency planning, timetable planning and rolling stock assignment problems and model the problem as a multi-commodity network flow problem considering competitive transport markets. The aim of the presented model is to maximize the total operator profit. We solve the optimization model using realistic probleminstances obtained from the network of the Spanish railwa operator RENFE, including other transport modes in Spai
In this work we tackle a real-world application of railway rolling stock planning, known as the trai...
Arising from a practical problem in German rail passenger transport, a prototype for a multi-period ...
AbstractIn the railway networks management context, the determination of train schedules is a topic ...
AbstractThe railway planning problem is usually studied from two different points of view: macroscop...
AbstractThe Train Timetabling Problem (TTP) has been widely studied for freight and passenger rail s...
The Train Timetabling Problem (TTP) has been widely studied for freight and passenger rail systems. ...
Airlines and high speed rail are increasingly competing for passengers, especially in Europe and Asi...
In this thesis, we address important optimization issues in railway operations planning, namely trai...
This paper focuses on optimizing the schedule of trains on railway networks composed of busy complex...
The definition of train scheduling is going to shift its current static approach, as generally resul...
The main aim of this work is to provide decision makers suitable approaches for solving two crucial ...
The aim of this paper is to propose an integrated planning model to adequate the offered capacity an...
Optimization models for railway traffic rescheduling tackle the problem of determining, in real-time...
This paper aims to develop a multi-objective model for scheduling cargo trains faced by the costs of...
HSR represents the future of medium-haul intercity transport. In fact, a number of HSR projects are ...
In this work we tackle a real-world application of railway rolling stock planning, known as the trai...
Arising from a practical problem in German rail passenger transport, a prototype for a multi-period ...
AbstractIn the railway networks management context, the determination of train schedules is a topic ...
AbstractThe railway planning problem is usually studied from two different points of view: macroscop...
AbstractThe Train Timetabling Problem (TTP) has been widely studied for freight and passenger rail s...
The Train Timetabling Problem (TTP) has been widely studied for freight and passenger rail systems. ...
Airlines and high speed rail are increasingly competing for passengers, especially in Europe and Asi...
In this thesis, we address important optimization issues in railway operations planning, namely trai...
This paper focuses on optimizing the schedule of trains on railway networks composed of busy complex...
The definition of train scheduling is going to shift its current static approach, as generally resul...
The main aim of this work is to provide decision makers suitable approaches for solving two crucial ...
The aim of this paper is to propose an integrated planning model to adequate the offered capacity an...
Optimization models for railway traffic rescheduling tackle the problem of determining, in real-time...
This paper aims to develop a multi-objective model for scheduling cargo trains faced by the costs of...
HSR represents the future of medium-haul intercity transport. In fact, a number of HSR projects are ...
In this work we tackle a real-world application of railway rolling stock planning, known as the trai...
Arising from a practical problem in German rail passenger transport, a prototype for a multi-period ...
AbstractIn the railway networks management context, the determination of train schedules is a topic ...