Erasmus Center for Optimization in Public Transport 1 Shunting passenger train units: Practical planning aspects Ramon Lentink, Pieter-Jan Fioole, Dennis.

Slides:



Advertisements
Similar presentations
Airline Schedule Optimization (Fleet Assignment I)
Advertisements

Capacity Planning. How much long-range capacity is needed When more capacity is needed Where facilities should be located (location) How facilities should.
Capacity Studies on Transportation Network Presented by Rakesh Ambre ( ) Under Guidance Of Prof. Narayan Rangaraj.
KTH Railway Group Center for research and education in Railway technology Railway Group Higher axle-loads Wider gauge End of Train Device (EOT) Electronic.
AchieveService Seminar 27 th April 2010 AchieveService Seminar.
EYYUP ORAK Material requirements planning (MRP) is a computer-based inventory management system designed to assist production managers in.
Train platforming problem Ľudmila Jánošíková Michal Krempl University of Žilina, VŠB-Technical University of Ostrava, Slovak Republic Czech Republic.
Rake Linking for Suburban Train Services. Rake-Linker The Rake-Linker assigns physical trains (rakes) to services that have been proposed in a timetable.
10 December J/ESD.204J Lecture 13 Outline Real Time Control Strategies for Rail Transit Prior Research Shen/Wilson Model Formulation Model Application.
Chapter 15 Application of Computer Simulation and Modeling.
Company confidential Prepared by HERE Transit Sr. Product Manager, HERE Transit Product Overview David Volpe.
Reinventing Crew Scheduling At Netherlands Railways Erwin Abbink, NS Reizigers bv, The Netherlands (NL) Matteo Fischetti, University of Padua, Italy Double.
Stochastic optimization of a timetable M.E. van Kooten Niekerk.
Maintenance Routing Gábor Maróti CWI, Amsterdam and NS Reizigers, Utrecht Models for Maintenance Routing 2nd AMORE Seminar, Partas, 30.
3rd ARRIVAL Review Meeting [Patras, 12 May 2009] – WP3 Presentation ARRIVAL – WP3 Algorithms for Robust and online Railway optimization: Improving the.
Supply Chain Design Problem Tuukka Puranen Postgraduate Seminar in Information Technology Wednesday, March 26, 2009.
Transportation and Assignment Problems
Erasmus Center for Optimization in Public Transport Bus Scheduling & Delays Dennis Huisman Joint work with: Richard Freling and.
Passenger travel behavior model in railway network simulation Ting Li Eric van Heck Peter Vervest Jasper Voskuilen Dept. Of decision and information sciences.
Quadratic Programming Model for Optimizing Demand-responsive Transit Timetables Huimin Niu Professor and Dean of Traffic and Transportation School Lanzhou.
Presented to: By: Date: File: apo130\Airport Efficiency\TAER SAER Updated Briefing(2).ppt 1030 Federal Aviation Administration Presentation of System Airport.
Rail Related Research at IIT Madras
RAILWAY INDUSTRY TRAIN PLANNING LEVEL 2 TRAINING Module 9 - The TOCs and Network Rail.
CS410 - BLUE GROUP Final Presentation communicate2Me.
2006 Palisade User ConferenceNovember 14 th, 2006 Inventory Optimization of Seasonal Products with.
Agenda Development of long distance Coach market in case of Germany APC- 10 year‘s anniversary meeting, Riga, 05. Septemer 2013.
Traffic Management System And Passenger Information System Western Railway Experience.
. Center TRACON Automation System (CTAS) Traffic Management Advisor (TMA) Transportation authorities around the globe are working to keep air traffic moving.
1 Botond Kovari: Crew Planning 1 st Int. Conf. on Research in Air Transportation - Zilina, Nov 22-24, 2004 Cost Optimisation Methods in Air Crew Planning.
MIT ICAT ICATMIT M I T I n t e r n a t i o n a l C e n t e r f o r A i r T r a n s p o r t a t i o n Virtual Hubs: A Case Study Michelle Karow
Anders Peterson Fahimeh Khoshniyat Dept. of Science and Technology Linköping University, Norrköping, Sweden 6 th May 2014 Effects of Travel Time Dependent.
Industrial Project (236504) Transportation task planning algorithms ClickSoftware Project Requirements Students: Noam Lavie, Ori Shalev Supervisors: Israel.
© 2012 Veritec Solutions Incorporated. All Rights Reserved. Potential Synergies from Positive Train Control Bruce Patty Vice President – Transportation.
Q/.r NSRZKLA4-P1 Capacity planning for railway systems Leo Kroon Jan 17, 2002.
Technical Analysis. Technical analysis of a project idea includes an in depth study of all technical aspects related to Technical analysis of a project.
Railway Operations: Issues and Objectives Capacity management Infrastructure planning Timetable preparation Management of day-to-day movement of trains.
A Joint Research Project funded under the Seventh Framework Programme (FP7) of the European Commission Innovations in Automated Planning.
An Evaluation of Heuristic Methods for Determining the Best Table Mix in Full-Service Restaurants Sheryl E. Kimes and Gary M. Thompson Cornell University.
CS4272 Hardware-Software Co-design Assignment 1 School of Computing National University of Singapore Guo Liang.
Company for Urban Innovative Transport (CUIT) 19/12/2007 Request for proposal.
Q/.r NSRZKLA4-P1 EUR team: Leo Kroon (EUR / NS)Timetable, rolling stock, crew Gabor Maroti (EUR / ARRIVAL)Timetable, rolling stock Ph.D. student (EUR /
Overview Presentation Fall 2015 Gainesville-Haymarket Extension Study.
Q/.r NSRZKLA4-P1 Timetable planning Leo Kroon Sept 9, 2003.
Strategies to cope with disruptions in urban public transportation networks Evelien van der Hurk Department of Decision and Information Sciences Complexity.
March 16, 2016A&MIS 5251 Session 28 A&MIS 525 May 8, 2002 William F. Bentz.
Maricopa Association of Governments (MAG) February 5, 2003.
© 2010 IBM Corporation IBM Container Transport Optimization Dr. Juergen Koehl, IBM Research and Development, Boeblingen Juergen Koehl, IBM Container Logistics.
Anytime, Anywhere Access Benefits Functionality Work Order Administration Dispatch Work Order Work Order Details New Work Order Additional Functionality.
Materials & Logistics Management
February 28 Assignments HW #8, 9, and 10 assigned Implementation plan
Dikos, George, and Stavroula Spyropoulou
August ICA Agenda Time Topic 8:00 – 8:15
The Unit Planner 2 – The Console Radio Broadcasting 4
Dutch railway quantities
Introduction to CS Senior Design Project I / II
A Modeling Framework for Flight Schedule Planning
Supply Chain Network and Optimization Executive Seminar
Introduction to CS Senior Design Project I / II
Introduction to CS Senior Design Project I / II
Gautrain System from An Operator’s Perspective
1.206J/16.77J/ESD.215J Airline Schedule Planning
Lesson 6 Wrap-Up.
Operations Research Lecture 2.
Structure of the final report
Sample ‘Scheduling Process’
Railways Research Foundation RAILWAYS EXPERTISE CENTER
King Saud University College of Engineering IE – 462: “Industrial Information Systems” Fall – 2018 (1st Sem H) Introduction (Chapter 1) part.
Introduction to Modeling
Introduction to CS Senior Design Project I / II
RTC RIDE Service Improvement Recommendations
Presentation transcript:

Erasmus Center for Optimization in Public Transport 1 Shunting passenger train units: Practical planning aspects Ramon Lentink, Pieter-Jan Fioole, Dennis Huisman, Leo Kroon Erasmus University Rotterdam, The Netherlands AMORE, 3 rd Research Seminar October 1 – 4, 2002, Oegstgeest, The Netherlands

Erasmus Center for Optimization in Public Transport 2 Contents Introduction to the problem Solution approach Demonstration of the prototype Summary

Erasmus Center for Optimization in Public Transport 3 Examples of train units MAT MAT ICM3 DD-IRM

Erasmus Center for Optimization in Public Transport 4 Layout of a station

Erasmus Center for Optimization in Public Transport 5 Problem aspects Railway station and surroundings Arriving and departing trains Coupling and uncoupling of units Mixed arrivals and departures within planning period Different types of units Different types of shunt tracks

Erasmus Center for Optimization in Public Transport 6 Shunting overview Routing train units Scheduling personnel Parking train units Cleaning and maintenance SHUNTING

Erasmus Center for Optimization in Public Transport 7 Problem definition Given –arriving shunt units, departing shunt units, shunt tracks and station infrastructure Match the arriving units and the departing units and assign each unit to a shunt track between arrival and departure if necessary, such that: –costs are minimized, the capacity of the shunt tracks is never exceeded and there are no conflicts between arriving and departing shunt units and through trains

Erasmus Center for Optimization in Public Transport 8 Solution approach 4 step approach: 1) Match supply and demand of train units 2) Generate efficient routes 3) Assign units to shunt tracks 4) Determine all final routes

Erasmus Center for Optimization in Public Transport 9 What´s new? Increased support for planner More accurate implementation (especially w.r.t. free tracks) Prototype evolved (e.g. input generation, integration with personnel planning, different views on the results) Application to a different station

Erasmus Center for Optimization in Public Transport 10 Computational results I Railway station Zwolle in the Netherlands 8 am - 8 am next morning in March shunt tracks, meters, 16 platforms 84 train units to be shunted during the day, meters Runtime third step ±8 minutes 731 shunt movements

Erasmus Center for Optimization in Public Transport 11 Computational results II Railway station Enschede in the Netherlands 8 am - 8 am next morning in March shunt tracks, meters, 4 platforms 28 train units to be shunted during the day, meters Runtime third step ±5 seconds 199 shunt movements

Erasmus Center for Optimization in Public Transport 12 The DEMO …

Erasmus Center for Optimization in Public Transport 13 Summary Short description of shunting problem and implemented solution approach Application of solution approach to Zwolle and Enschede Demo of the prototype decision support system