| People | Locations | Statistics |
|---|---|---|
| Ziakopoulos, Apostolos | Athens |
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| Vigliani, Alessandro | Turin |
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| Catani, Jacopo | Rome |
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| Statheros, Thomas | Stevenage |
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| Utriainen, Roni | Tampere |
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| Guglieri, Giorgio | Turin |
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| Martínez Sánchez, Joaquín |
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| Tobolar, Jakub |
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| Volodarets, M. |
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| Piwowar, Piotr |
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| Tennoy, Aud | Oslo |
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| Matos, Ana Rita |
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| Cicevic, Svetlana |
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| Sommer, Carsten | Kassel |
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| Liu, Meiqi |
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| Pirdavani, Ali | Hasselt |
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| Niklaß, Malte |
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| Lima, Pedro | Braga |
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| Turunen, Anu W. |
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| Antunes, Carlos Henggeler |
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| Krasnov, Oleg A. |
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| Lopes, Joao P. |
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| Turan, Osman |
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| Lučanin, Vojkan | Belgrade |
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| Tanaskovic, Jovan |
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MANNINO, CARLO
in Cooperation with on an Cooperation-Score of 37%
Topics
- railway train
- algorithm
- human being
- prevention
- scheduling
- corporation
- railway network
- human error
- railway company
- air traffic
- air traffic control
- beltway
- crash
- simulation
- estimating
- software
- region
- airport
- constraint
- bottleneck
- highway traffic control
- occupation
- airplane
- timetable
- shopping facility
- infrastructure
- timetable scheduling
- single track
- railway traffic
- flexibility
- expansion
- modernization
- rolling stock
- two-rail track
- double track
- property
- managerial personnel
- passenger
- optimisation
- vehicle occupant
- hub
- autumn
- prototype
- deviation
- dispatching
- passenger train
- dispatcher
- main station
- traffic control
- industry
- abstract
- modeling
- operations research
- computer science
- control device
- variable
- flight
- definition
- departure time
- management science
- supporting
- airspace
- workload
- air traffic controller
- vehicle
- routing
- surveillance
- learning
- experiment
- laceration
- aircraft pilotage
- public transport
- transportation engineering
- decision making
- economic growth
- committee
- air shipment
- sustainable development
- aviation
- airline
- aerospace engineering
- attention
- implementation
- design
- regional railway
- landing
- machinery
- engineering
- mixed integer programming
- airport runway
- sequencing
- taxicab
- pressure
- decomposition
- tower
- emergency response time
- commodity
- control system
- shipment
- linear programming
- traffic control system
- costs
- railway station
- show 73 more
Publications (16/16 displayed)
- 2022Easy Cases of Deadlock Detection in Train Schedulingcitations
- 2022Scheduling Vehicles with Spatial Conflicts
- 2022A MILP model for quasi-periodic strategic train timetablingcitations
- 2022Disruption management in railway systems by safe place assignment
- 2022Optimal Train Rescheduling in Oslo Central Stationcitations
- 2021The Tick Formulation for deadlock detection and avoidance in railways traffic controlcitations
- 2020Air Traffic Flow Management with Layered Workload Constraintscitations
- 2020Generalized Periodic Vehicle Routing and Maritime Surveillancecitations
- 2020Combinatorial Learning in Traffic Management
- 2019Can Holistic Optimization Improve Airport Air Traffic Management Performance
- 2018Train Dispatchingcitations
- 2017Optimal design of a regional railway service in Italycitations
- 2017Time-Indexed Formulations for the Runway Scheduling Problemcitations
- 2013Integrated surface and departure management at airports by optimizationcitations
- 2011Real-time traffic control in railway systems
- 2009Optimal Real-Time Traffic Control in Metro Stationscitations
Places of action
booksection
Train Dispatching
Abstract
Train rescheduling problems have received significant attention in the operations research community during the past 20–30 years. These are complex problems with many aspects and constraints to consider. This chapter defines the problem and summarizes the variety of model types and solution approaches developed over the years, in order to address and solve the train dispatching problem from the infrastructure manager perspective. Despite all the research efforts, it is, however, only very recently that the railway industry has made significant attempts to explore the large potential in using optimization-based decision-support to facilitate railway traffic disturbance management. This chapter reviews state-of-practice and provides a discussion about the observed slow progress in the application of optimization-based methods in practice. A few successful implementations have been identified, but their performance as well as the lessons learned from the development and implementation of those system are unfortunately only partly available to the research community, or potential industry users ; Train Dispatching ; acceptedVersion
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