Downloaded from orbit.dtu.dk on: Oct 05, 2021 The Train Driver Recovery Problem - Solution Method and Decision Support System Framework Rezanova, Natalia Jurjevna Publication date: 2009 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Rezanova, N. J. (2009). The Train Driver Recovery Problem - Solution Method and Decision Support System Framework. DTU Management PhD thesis No. 4.2009 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. Users may download and print one copy of any publication from the public portal for the purpose of private study or research. You may not further distribute the material or use it for any profit-making activity or commercial gain You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. The Train Driver Recovery Problem – Solution Method and Decision Support System Framework Natalia J. Rezanova Kgs. Lyngby, Denmark, 2009 DTU Management Engineering Department of Management Engineering Technical University of Denmark Produktionstorvet, building 424 DK-2800 Kgs. Lyngby, Denmark Phone +45 45 25 48 00, Fax +45 45 25 48 05 www.man.dtu.dk Preface This thesis is prepared at DTU Management Engineering Department, the Technical University of Denmark, in partial fulfillment of the requirements for acquiring the Degree of Doctor of Philosophy (Ph.D.) in Engineering Science. The main focus of this thesis is on state-of-the-art Operations Research meth- ods applied within the area of disruption management in public railway in- dustry, particular within the train driver recovery. An optimization solution method to the train driver recovery problem is proposed, and a prototype for train driver dispatchers decision support system is developed. The project is carried out in a cooperation with a Danish passenger railway operator DSB S-tog A/S. The Ph.D. project is supervised by professor Jens Clausen, who is also a part- time chief analyst at DSB S-tog A/S. A substantial scientific contribution to this project is provided by the supervision of professor David M. Ryan, De- partment of Engineering Science, The University of Auckland, New Zealand, who is also a visiting professor at the Technical University of Denmark. Kgs. Lyngby, Denmark, May 2009 Natalia J. Rezanova ii Abstract In this thesis we consider the train driver recovery problem (TDRP). The problem occurs when the daily train driver schedule becomes infeasible due to irregular operations on the railway network. Unforeseen disruptions such as signalling problems or rolling stock failures prevent the train drivers from following the originally scheduled sequence of activities in their duties. The real-time re-scheduling of the disrupted train driver duties is currently per- formed manually by the train driver dispatchers. If the disruption is severe and many train driver duties are disturbed, this is a very complicated task to carry out. The interest of the passenger railway operator DSB S-tog A/S in introducing automated decision support for the train driver dispatchers is a key motivation for this project. We propose an optimization-based solution method for solving the TDRP and develop a prototype for the decision support system. The framework is based on solving restricted TDRP instances with a rolling time horizon, aiming at modifying the original duty schedule as little as possible. We for- mulate TDRP as a set partitioning model, where variables represent train driver recovery duties, and describe why the proposed model and solution method is suitable for solving in real-time. Recovery duties are generated as resource constrained paths in duty networks, and the set partitioning prob- lem is solved with a linear programming based branch-and-price algorithm. Dynamic column generation and problem space expansion at each node of the branch-and-price tree together with a constraint branching strategy con- iv tribute to the solution method. Real-life operational data is provided by DSB S-tog A/S in order to test the implemented solution method. Based on the computational experiments presented in this thesis, we conclude that the proposed approach is indeed applicable for implementation in a decision support system for train driver dispatchers in practice. DSB S-tog A/S is working on using the research re- sults obtained during this thesis and the programming code of the prototype to develop and implement the train driver decision support system in their operational environment. Besides solving a particular optimization problem, this thesis contributes with a description of the railway planning process, tactical crew schedul- ing and the real-time dispatching solutions, taking a starting point in DSB S-tog’s operations. Furthermore, we present comprehensive reviews of op- erations research applications within railway crew scheduling, rolling stock re-scheduling, railway crew re-scheduling, and airline crew recovery. In addi- tion, the project has resulted in the three scientific publications listed below. 1. Rezanova NJ, Ryan DM. The train driver recovery problem–A set par- titioning based model and solution method. Computers and Operations Research, in press, 2009. doi: 10.1016/j.cor.2009.03.023. 2. Clausen J, Larsen A, Larsen J, Rezanova NJ. Disruption management in the airline industry–Concepts, models and methods. Computers and Operations Research, in press, 2009. doi: 10.1016/j.cor.2009.03.027. 3. Rezanova NJ, Ryan DM. The train driver recovery problem–A set par- titioning based model and solution method. IMM-Technical Report- 2006-24. Informatics and Mathematical Modelling, Technical Univer- sity of Denmark, 2006. Available at http://www2.imm.dtu.dk/pubdb/p.php?5157. Resum´e Hovedform˚alet med denne afhandling er at anvende state-of-the-art opera- tionsanalytiske metoder inden for realtidsdisponering ifm. jernbanedrift. Ar- bejdet er udført i samarbejde med DSB S-tog A/S og omhandler problemet med genopretning af tjenesteplaner for lokomotivførere (the train driver re- covery problem, TDRP). Problemet opst˚ar, n˚ar den daglige tjenesteplan for lokomotivførere ikke længere kan opretholdes p˚agrund af uregelmæssigheder p˚ajernbanenetværket. Uventede driftsforstyrrelser s˚asomsignalfejl eller ned- brud af tog forhindrer lokomotivførere i at følge deres oprindelige tjenester. Realtidsdisponering og genopretning af de afbrudte tjenester udføres p˚anu- værende tidspunkt manuelt af personaledisponenter. Omfættende drifts- forstyrrelser p˚avirker mange tjenester, og genopretning af lokomotivførerplanen bliver kompliceret og uoverskuelig. Hovedmotivationen for dette projekt er DSB S-togs interesse for at udvikle et automatisk beslutningsstøttesystem til personaledisponenterne er . Vi designer en optimeringsbaseret løsningsmetode til TDRP og udvikler en prototype til beslutningsstøttesystemet. Fremgangsm˚aden er at løse sm˚a TDRP instanser over en rullende tidshorisont. Hver TDRP er rettet mod at bygge genopretningstjenester samtidig med at ændre den oprindelige tjen- esteplan s˚alidt som muligt. Vi formulerer TDRP som et set partition- ing problem, hvor beslutningsvariablene repræsenterer genopretningstjen- ester. Vi beskriver, hvorfor den forsl˚aedemodel og løsningsmetoden er veleg- net til realtidsdisponering. Genopretningstjenesterne genereres som korteste vi veje med ressourcebegrænsninger i et specielt byggede tjenestenetværk. Set partitioning problemet løses med en branch-and-price metode. Dynamisk søjlegenerering og dynamisk udvidelse af løsningsrummet sammen med con- straint branching som forgreningsstrategi bidrager til løsningsmetodens ef- fektivitet. DSB S-tog A/S har leveret operationelt datagrundlag til at teste den imple- menterede løsningsmetode. Baseret p˚ade gennemførte eksperimenter, kon- kluderer vi, at løsnings-metoden i høj grad er egnet til beslutningsstøtte i praksis. DSB S-tog A/S arbejder p˚aat bruge de videnskabsmæssige resul- tater og programkoden fra den udviklede prototype til udvikling af beslut- ningsstøtte i det operationelle miljø. Udover at løse et bestemt optimeringsproblem, giver denne afhandling med udgangs-punkt i DSB S-togs drift en beskrivelse af planlægningsprocesser i jernbanedrift, mandskabsplanlægning p˚adet taktiske niveau og realtids disponeringsstrategier. Ydermere præsenterer vi omfattende redegørelser for operationsanalytiske anvendelser med referencer inden for mandskabsplan- lægning ifm. jernbanedrift, materieldisponering, og mandskabsdisponering inden for jernbane og luftfart. Afhandling har desuden resulteret i følgende tre publikationer: 1. Rezanova NJ, Ryan DM. The train driver recovery problem–A set par- titioning based model and solution method. Computers and Operations Research, in press, 2009. doi: 10.1016/j.cor.2009.03.023. 2. Clausen J, Larsen A, Larsen J, Rezanova NJ. Disruption management in the airline industry–Concepts, models and methods. Computers and Operations Research, in press, 2009. doi: 10.1016/j.cor.2009.03.027. 3. Rezanova NJ, Ryan DM. The train driver recovery problem–A set par- titioning based model and solution method. IMM-Technical Report- 2006-24. Informatics and Mathematical Modelling, Technical