Railway systems occasionally get into a state of being out-of-control, meaning that barely any train is running, even though the required resources (infrastructure, rolling stock and crew) are available. Because of the large number of affected resources and the absence of detailed, timely and accurate information, currently existing disruption management techniques cannot be applied in out-of-control situations. Most of the contemporary approaches assume that there is only one single disruption with a known duration, that all information about the resources is available, and that all stakeholders in the operations act as expected. Another limitation is the lack of knowledge about why and how disruptions accumulate and whether this process can be predicted. To tackle these problems, we develop a multidisciplinary framework combining techniques from complexity science and operations research, aiming at reducing the impact of these situations and—if possible—avoiding them. The key elements of this framework are (i) the generation of early warning signals for out-of-control situations, (ii) isolating a specific region such that delay stops propagating, and (iii) the application of decentralized decision making, more suited for information-sparse out-of-control situations.
@article{Dekker2022,author={Dekker, Mark M. and van Lieshout, Rolf N. and Ball, Robin C. and Bouman, Paul C. and Dekker, Stefan C. and Dijkstra, Henk A. and Goverde, Rob M. P. and Huisman, Dennis and Panja, Debabrata and Schaafsma, Alfons A. M. and van den Akker, Marjan},title={A next step in disruption management: combining operations research and complexity science},journal={Public Transport},year={2022},month=mar,day={01},volume={14},number={1},pages={5--26},issn={1613-7159},doi={10.1007/s12469-021-00261-5},url={https://doi.org/10.1007/s12469-021-00261-5}}
2021
Oct 2021
EP*
A self-organizing policy for vehicle dispatching in public transit systems with multiple lines
@article{van_Lieshout_2021,doi={10.1016/j.trb.2021.08.004},url={https://doi.org/10.1016%2Fj.trb.2021.08.004},year={2021},month=oct,publisher={Elsevier {BV}},volume={152},pages={46--64},author={van Lieshout, Rolf N. and Bouman, Paul C. and van den Akker, Marjan and Huisman, Dennis},title={A self-organizing policy for vehicle dispatching in public transit systems with multiple lines},journal={Transportation Research Part B: Methodological}}
2020
Oct 2020
P*
Determining and Evaluating Alternative Line Plans in Out-of-Control Situations
From time to time, large disruptions cause heavily utilized railway networks to get into a state of out-of-control, in which hardly any trains are able to run as the result of a lack of accurate and up-to-date information available to dispatchers. In this paper, we develop and test disruption management strategies for dealing with these situations. First, we propose an algorithm that finds an alternative line plan that can be operated in the affected part of the railway network. As the line plan should be feasible with respect to infrastructural and resource restrictions, we integrate these aspects in the algorithm in a Benders-like fashion. Second, to operate the railway system within the disrupted region, we propose several local train dispatching strategies requiring varying degrees of flexibility and coordination. Computational experiments based on disruptions in the Dutch railway network indicate that the algorithm performs well, finding workable and passenger-oriented line plans within a couple of minutes. Moreover, we also demonstrate in a simulation study that the produced line plans can be operated smoothly without depending on central coordination.
@article{van_Lieshout_2020,author={van Lieshout, Rolf N. and Bouman, Paul C. and Huisman, Dennis},title={Determining and Evaluating Alternative Line Plans in Out-of-Control Situations},journal={Transportation Science},volume={54},number={3},pages={740-761},year={2020},doi={10.1287/trsc.2019.0945},url={https://doi.org/10.1287/trsc.2019.0945},eprint={https://doi.org/10.1287/trsc.2019.0945}}
Oct 2020
A New Sequential Approach to Periodic Vehicle Scheduling and Timetabling
Paul Bouman,
Alexander Schiewe,
and Philine Schiewe
In 20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2020)
When evaluating the operational costs of a public transport system, the most important factor is the number of vehicles needed for operation. In contrast to the canonical sequential approach of first fixing a timetable and then adding a vehicle schedule, we consider a sequential approach where a vehicle schedule is determined for a given line plan and only afterwards a timetable is fixed. We compare this new sequential approach to a model that integrates both steps. To represent various operational requirements, we consider multiple possibilities to restrict the vehicle circulations to be short, as this can provide operational benefits. The sequential approach can efficiently determine public transport plans with a low number of vehicles. This is evaluated theoretically and empirically demonstrated for two close-to real-world instances.
@inproceedings{bouman_et_al:OASIcs:2020:13142,author={Bouman, Paul and Schiewe, Alexander and Schiewe, Philine},title={{A New Sequential Approach to Periodic Vehicle Scheduling and Timetabling}},booktitle={20th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2020)},pages={6:1--6:16},series={OpenAccess Series in Informatics (OASIcs)},isbn={978-3-95977-170-2},issn={2190-6807},year={2020},volume={85},editor={Huisman, Dennis and Zaroliagis, Christos D.},publisher={Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},address={Dagstuhl, Germany},url={https://drops.dagstuhl.de/opus/volltexte/2020/13142},urn={urn:nbn:de:0030-drops-131422},doi={10.4230/OASIcs.ATMOS.2020.6},annote={Keywords: Vehicle Scheduling, Timetabling, Integrated Planning}}
2018
Oct 2018
Vehicle Scheduling Based on a Line Plan
Rolf N. van Lieshout,
and Paul C. Bouman
In 18th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2018)
We consider the following problem: given a set of lines in a public transportation network with their round trip times and frequencies, a maximum number of vehicles and a maximum number of lines that can be combined into a vehicle circulation, does there exist a set of vehicle circulations that covers all lines given the constraints. Solving this problem provides an estimate of the costs of operating a certain line plan, without having to compute a timetable first. We show that this problem is NP-hard for any restriction on the number of lines that can be combined into a circulation which is equal to or greater than three. We pay special attention to the case where at most two lines can be combined into a circulation, which is NP-hard if a single line can be covered by multiple circulations. If this is not allowed, a matching algorithm can be used to find the optimal solutions, which we show to be a 16/15-approximation for the case where it is allowed. We also provide an exact algorithm that is able to exploit low tree-width of the so-called circulation graph and small numbers of vehicles required to cover single circulations.
@inproceedings{vanlieshout_et_al:OASIcs:2018:9720,author={van Lieshout, Rolf N. and Bouman, Paul C.},title={{Vehicle Scheduling Based on a Line Plan}},booktitle={18th Workshop on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2018)},pages={15:1--15:14},series={OpenAccess Series in Informatics (OASIcs)},isbn={978-3-95977-096-5},issn={2190-6807},year={2018},volume={65},editor={Bornd{\"o}rfer, Ralf and Storandt, Sabine},publisher={Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},address={Dagstuhl, Germany},url={http://drops.dagstuhl.de/opus/volltexte/2018/9720},urn={urn:nbn:de:0030-drops-97204},doi={10.4230/OASIcs.ATMOS.2018.15},annote={Keywords: Vehicle scheduling, integrated railway planning, (fractional) matching, treewidth}}
Oct 2018
Dynamic programming approaches for the traveling salesman problem with drone
@article{Bouman_2018,doi={10.1002/net.21864},url={https://doi.org/10.1002%2Fnet.21864},year={2018},month=oct,publisher={Wiley},author={Bouman, Paul and Agatz, Niels and Schmidt, Marie},title={Dynamic programming approaches for the traveling salesman problem with drone},journal={Networks}}
Aug 2018
P*
Optimization Approaches for the Traveling Salesman Problem with Drone
@article{Agatz_2018,doi={10.1287/trsc.2017.0791},url={https://doi.org/10.1287%2Ftrsc.2017.0791},year={2018},month=aug,publisher={Institute for Operations Research and the Management Sciences ({INFORMS})},volume={52},number={4},pages={965--981},author={Agatz, Niels and Bouman, Paul and Schmidt, Marie},title={Optimization Approaches for the Traveling Salesman Problem with Drone},journal={Transportation Science}}
2017
Aug 2017
P*
The Travelers Route Choice Problem Under Uncertainty: Dominance Relations Between Strategies
@article{schmidt2017,author={Schmidt, Marie and Kroon, Leo and Sch\"{o}bel, Anita and Bouman, Paul},title={The Travelers Route Choice Problem Under Uncertainty: Dominance Relations Between Strategies},journal={Operations Research},volume={65},number={1},pages={184-199},year={2017},doi={10.1287/opre.2016.1564}}
2016
Aug 2016
Rotterdam: Revenue Management in Public Transportation with Smart-Card Data Enabled Agent-Based Simulations
Paul Bouman,
and Milan Lovric
Book Chapter in The Multi-Agent Transport Simulation MATSim
@incollection{bouman2016matsim,author={Bouman, Paul and Lovric, Milan},title={Rotterdam: Revenue Management in Public Transportation with Smart-Card Data Enabled Agent-Based Simulations},editor={Horni, Andreas and Nagel, Kai and Axhausen, Kay},booktitle={The Multi-Agent Transport Simulation MATSim},publisher={Ubiquity Press},address={London},year={2016},pages={477--480},chapter={81},doi={10.5334/baw.81}}
Aug 2016
P
Decomposition approaches for recoverable robust optimization problems
@article{van2016decomposition,title={Decomposition approaches for recoverable robust optimization problems},author={van den Akker, Marjan and Bouman, Paul and Hoogeveen, Han and {T{\"o}nissen}, Denise},journal={European Journal of Operational Research},volume={251},number={3},pages={739--750},year={2016},publisher={Elsevier},doi={10.1016/j.ejor.2015.12.008}}
Sep 2016
S
Capacity, information and minority games in public transport
P.C. Bouman,
Leo Kroon,
Peter Vervest,
and Gábor Maróti
Transportation Research Part C: Emerging Technologies
@article{Bouman_2016,doi={10.1016/j.trc.2016.05.007},url={https://doi.org/10.1016%2Fj.trc.2016.05.007},year={2016},month=sep,publisher={Elsevier {BV}},volume={70},pages={157--170},author={Bouman, P.C. and Kroon, Leo and Vervest, Peter and Mar{\'{o}}ti, G{\'{a}}bor},title={Capacity, information and minority games in public transport},journal={Transportation Research Part C: Emerging Technologies}}
2013
Sep 2013
Passenger Route Choice in Case of Disruptions
Paul Bouman,
Marie Schmidt,
Leo Kroon,
and Anita Schöbel
In Proceedings of the 16th International IEEE Conference on Intelligent Transport Systems
@inproceedings{bouman2013,author={Bouman, Paul and Schmidt, Marie and Kroon, Leo and Sch\"obel, Anita},title={Passenger Route Choice in Case of Disruptions},booktitle={Proceedings of the 16th International IEEE Conference on Intelligent Transport Systems},year={2013},doi={10.1109/ITSC.2013.6728370}}
Nov 2013
Detecting Activity Patterns from Smart Card Data
Paul Bouman,
Evelien van der Hurk,
Leo Kroon,
Ting Li,
and Peter Vervest
In Proceedings of the 25th Benelux Conference on Artificial Intelligence
During the past decades, the modelling of transport demand by activity based methods has gained considerable attention from the scientific community. Such demand models offer a greater modelling flexibility than traditional models, by modelling transport demand as a phenomenon which emerges from the desire to perform activities at different locations, as opposed to more traditional models where an origin destination demand matrix of trips is distributed over different routes and modes. One of the drawbacks of the activity based paradigm is that data related to activities is more difficult to collect than traffic counts. Modern technologies, such as smart card ticketing systems and smart phones, allow us to collect more detailed accounts of the movements of individual passengers. This gives us the possibility to analyse consecutive journeys and therefore the time a passenger spends in a certain location. This information can be very useful from an activity based modelling perspective. In this paper we take an exploratory approach to derive important activity time intervals from smart card data. We apply a clustering algorithm on the intervals observed at individual stations to detect which time intervals capture enough activities. We then construct a tree-based labelling algorithm that allows us to label the activities and analyse activity chains of individual passengers. We count pairs of consecutive activity labels, visualise the results as a network and calculate which triplets of consecutive activities occur most often. Using this approach, we are able to identify activity patterns that differ from the typical time windows associated with home-work activities.
@inproceedings{boumanSmartCard,title={Detecting Activity Patterns from Smart Card Data},author={Bouman, Paul and van der Hurk, Evelien and Kroon, Leo and Li, Ting and Vervest, Peter},booktitle={Proceedings of the 25th Benelux Conference on Artificial Intelligence},editor={Hindriks, Koen and de Weerdt, Mathijs and van Riemsdijk, Birna and Warnier, Martijn},year={2013},month=nov,url={http://resolver.tudelft.nl/uuid:a7b14dbd-1501-405f-bf2e-12886268d804}}
2012
Nov 2012
Recognizing Demand Patterns from Smart Card Data for Agent-Based Micro-simulation of Public Transport
Paul Bouman,
Milan Lovric,
Ting Li,
Evelien van der Hurk,
Leo Kroon,
and Peter Vervest
In Proceedings of the Seventh Workshop on Agents In Traffic and Transportation
@inproceedings{bouman2012att,author={Bouman, Paul and Lovric, Milan and Li, Ting and van der Hurk, Evelien and Kroon, Leo and Vervest, Peter},title={Recognizing Demand Patterns from Smart Card Data for Agent-Based Micro-simulation of Public Transport},booktitle={Proceedings of the Seventh Workshop on Agents In Traffic and Transportation},year={2012},url={http://www.ia.urjc.es/att2012/papers/att2012_submission_21.pdf}}
@incollection{Bouman2011ESA,year={2011},isbn={978-3-642-23718-8},booktitle={Algorithms ESA 2011},volume={6942},series={Lecture Notes in Computer Science},editor={Demetrescu, Camil and Halldorsson, Magn\'us M.},doi={10.1007/978-3-642-23719-5\_19},title={Recoverable Robustness by Column Generation},publisher={Springer Berlin Heidelberg},author={Bouman, Paul and van den Akker, Marjan and Hoogeveen, Han},pages={215-226},language={English}}
The P*, EP*, P and S labels indicate the position of the different journals on the ERIM Journal List.