07.03.05 07002-irse-bris2007-rail sched-finaldrc

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A presentation accompanying a paper on the subject of railway schedule optimisation and infrastructure optioneering.
Presented before the Institution Of Railway Engineers in 2007 by author David Caldwell

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  • Firstly, to clear up the subject of this paper, the interest is specifically in the train planning aspect of scheduling.
  • … the elements of the process are illustrated here…
  • Constraints include dependencies between services, e.g. the train running into the balloon becoming a new train ID on the way out
  • We have quite a complex process. As is the case with many processes when you are seeking better performance, better productivity, the question arises, “is there some way of automating this process to speed it up, or get better information” This problem is what led researchers Scott Mackenzie and Peter Pudney of the University of South Australia to investigate the application of Problem Space Search
  • Valid timetables are ones which satisfy constraints such as safeworking and not producing deadlock, That is, situations where there are two trains approaching each-other with no possibility of either one refuging in the intervening sections Deadlocked timetables can just be discarded
  • By “quality” is potentially whatever quantitative KPI you want to apply, whether it be average delay, delay cost, fuel use, etc The software developed around Problem Space Search takes this basic form…
  • [Progressive reveal, explain each] Working through examples of these inputs an outputs…
  • Here we can see a geography description from NSW, with each of the [progressive reveal] key operational features of the line
  • This is quite a busy train graph, illustrating the interaction between normal and high priority trains If we look at a small section [progressive reveal] It can be seen that the green trains have been stopped for passes whereas the red trains have proceeded unimpeded (except for station stops)
  • I will return to this subject with my second case study on ARTC
  • Here it can be seen that rather than specifying a train type and origin and destination, the user configures availability and type of ore at the mine loader
  • Thanks to WorleyParsons for providing the time to prepare this paper Alex Wardrop who is the co-author Pascal Sueess for his review James Moor of the ARTC for providing information on the strategic planning applications We also thank the University of South Australia and the CRC for supporting the recent development of the Problem Space Search technique
  • 07.03.05 07002-irse-bris2007-rail sched-finaldrc

    1. 1. IRSE 2007 Technical Conference- BrisbaneApplication of Problem Space Search to Heavy HaulSchedulingAlex WARDROP & David CALDWELL
    2. 2. What is scheduling?  “Scheduling” is a broad term and can include crew rostering, maintenance scheduling and train planning (timetabling)  Here the main interest is train planning  Train plans may be developed around the constraints of crew rostering, and in cooperation with maintenance scheduling2 07/02/12
    3. 3. Train Planning  Train planning is placing a set of train requirements over a railway network  Train requirements are the trips that train operators want to operate over a given period of time to meet commercial requirements (moving stuff)  The aim of the train planner is to move these trains to their required destinations with as little delay as possible3 07/02/12
    4. 4. Train Planning Train demand (e.g. Network (e.g. running times, trains, origins, stops, Maintenance loop lengths, safeworking, destinations) requirements loader capacity) Train performance and requirements Crew rostering/ Otherindustrial requirements Constraints Maintenance Train planning scheduling Day of Operation planning Maintenance Operations4 07/02/12
    5. 5. Developing a timetable  In a manual process, the highest priority trains are “drawn” on the plan first  Lower priority trains are stopped for passes in preference to stopping high priority trains • Order of priority- “two legs, four legs, no legs”  This means that passenger trains go through the route on the minimum running times5 07/02/12
    6. 6. The heavy-haul problem  While the most densely utilised heavy-haul lines are double track, the majority of Australia’s heavy-haul track mileage is on single-track line  A major challenge is figuring out how to stop and pass trains, and when to admit them to the next section  This has to be done with consideration for both safeworking requirements and refuging opportunities  A train plan looks like this, showing the train ID and stops Distance  Lines are coloured to represent an important attribute, like train length, running time, or priority6 07/02/12 Time
    7. 7. What is Problem Space Search?  Unlike a mathematical algorithm which seeks to find an exact solution, Problem Space Search employs a heuristic (or trial and error mathematical process) to develop many feasible solutions to a problem  These solutions can then be scored against an objective function and ranked  Research undertaken jointly by the University of South Australia and the former TMG International found that the technique was applicable to rail scheduling7 07/02/12
    8. 8. Application of Problem Space Search  By applying perturbations to crossing delays of trains moving through a network, the order in which trains meet is varied, and so the orders of crossings changed  Thousands of different valid train plans can be generated in a matter of seconds  These valid solutions can then be evaluated and ranked for their performance against criteria such as delays and cost8 07/02/12
    9. 9. Application of Problem Space Search  Developing a timetable by manual techniques generally takes months  An automated train plan optimising technique has obvious direct benefits for train planning, reducing the time to produce a timetable, and improving its “quality”  The huge reduction in the effort required to develop a timetable means that timetables can be quickly manipulated very close to the implementation horizon, and still produce optimal results  Timetables can also be easily developed for speculative purposes (“what if…” scenarios)  Software using Problem Space Search for these purposes has been developed9 07/02/12
    10. 10. Information flow TRAIN CHARACTERISTICS RAIL NETWORK DESCRIPTION Length Track layout Running time class Refuge locations Priority INPUT TRAIN REQUIREMENTS Junction locations Nominal despatch times Sectional running times Days of operation Safeworking systems Dwell times RailSched Dependencies between services Near-optimal Line Capacity timetable report10 07/02/12
    11. 11. Typical InputsTrack Infrastructure- links and nodes Bi-directional line Refuge Crossovers Uni-directional line Station name Crossing loop11 07/02/12
    12. 12. Output: optimised train plan BW4 is a high priority train MB3 is a low priority train12 07/02/12
    13. 13. Output: Capacity utilisation13 07/02/12
    14. 14. Application  The Problem Space Search technique is applied for both timetabling and strategic infrastructure planning  An integrated scheduling system, ScheduleMiser ™ was developed for BHP Billiton  A more general scheduling tool, Rail//Sched ™ is the subject of ongoing development for the Australian Rail Track Corporation  In both cases the general data requirements and outputs are the same, thought the interfaces differ significantly, according to specific requirements14 07/02/12
    15. 15. Case study: ScheduleMiser  ScheduleMiser was developed to represent BHP Billition’s iron ore moving process, rather than looking at trains in isolation Material at mine loader Time it takes to load a rake Time it takes to re-stack the stockpile at the loader Desirability of different rake configurations15 07/02/12
    16. 16. Translating BHP requirements  The user specifies production requirements, as well as other operational variables like loader availability and rake locations  ScheduleMiser builds trains of one, two or three rakes to satisfy production  Day to day operational conditions, like TSRs and track possessions, are also configured16 07/02/12
    17. 17. The BHP requirement Ore requirements at Shipping port Rolling stock, mine, Track availability unloader and network (possessions) configuration ScheduleMiser Dumper report Rake report Optimised timetables and train plan17 07/02/12
    18. 18. Typical schedule output  The user configures all the requirements and runs the schedule resolver  A train plan, similar to the following, is resolved18 07/02/12
    19. 19. Planning close to the horizon  Need to be able to rapidly review timetable for changing train requirements, e.g. out of order running  Developing amended timetables close to the event  WorleyParsons, with the assistance of a Commercial Ready grant, is currently integrating automated scheduling with real-time GPS train location information  Train locations can be continuously updated in the model, and a timetable with minimum delay calculated almost immediately  There is another significant application of automatic timetable generation…19 07/02/12
    20. 20. Strategic Infrastructure Planning  Why different scheduling scenarios need to be considered • Which loops should be lengthened or moved? • Will changing the safeworking system (i.e. eliminating token exchange delays) have a practical effect on capacity? • Will automating points (and reducing route-setting delays) and improving turn-out speeds have a practical effect? • What is the effect of running some longer trains which are excluded from more loops?20 07/02/12
    21. 21. Considering the future DEMAND SCENARIOS OPERATIONS SCENARIOS SCHEDULING INFRA - TRAINS STRUCTRE WHAT IS THE MOST COST -EFFECTIVE?21 07/02/12
    22. 22. Case Study: Rail//Sched  The ARTC is developing its network for expected traffic growth  Their 2005 Hunter Valley strategy anticipates that from 2006 to 2010, tonnage between Musswellbrook and Antiene will approximately triple from about 20MTpa to about 60MTpa22 07/02/12
    23. 23. 2307/02/12 From ARTC 2005 Hunter Valley Coal Network Capacity Improvement Strategy, figure A, pii Hunter Valley growth
    24. 24. The effect of growth  ARTC developed infrastructure improvement plans to satisfy this growth  To verify that delay would remain at an acceptable level, ARTC developed proposed infrastructure schemes (varying over time), and then developed experimental future train requirements to meet operators’ train requirements/ tonnages  ARTC then used Rail//Sched to generate hypothetical timetables for the increased network usage  Once these timetables were generated, they were assessed for relative changes in delay compared with current operations24 07/02/12
    25. 25. ARTC’s application Develop input timetables  Expectedly, when traffic (train types and despatch times of projected traffic) levels increase, but the Describe infrastructure scenario (s) network remains Pre-process (add noise to despatch times) unchanged, average delay per train and travel RAIL//SCHED times increase  The process applied to assess infrastructure improvements… Optimised timetables Average Delays Post processing (Excel) Normalised dimensionless delay25 07/02/12
    26. 26. ARTC’s application  The types of network variables that are typically considered are safeworking, loop lengths, loop locations and additional tracks  One component of ARTC’s strategy to meet projected demand is the Antiene to Grasstree duplication  Duplication by 2008, proposed in the strategy, reduces delays to below the levels in early 200626 07/02/12
    27. 27. Modelling delay Modelled Hunter Valley Network Performance 35 MUA Expected delay per train SLR GTR Delay per train reducing (dimensionless time) 30 in first half of 2008 ANT 25 4th quarter 2006 DRJ 1st quarter 2007 20 2nd quarter 2007 3rd quarter 2007 4th quarter 2007 15 1st quarter 2008 2nd quarter 2008 NDC 10 NJM Duplication of Antiene - ACS Grasstree in MOC 5 first half of BNX MBH 2008 BEL WHM MB1 MDX SGL CAM KIY 0 NEWCASTLE MUSWELLBROOK27 07/02/12
    28. 28. Benefit for planning  Being able to quickly generate these speculative train plans (and calculate delay) is very helpful for considering • Whether a proposed infrastructure plan is a going to satisfy requirements • Which projects should take priority • Whether changing traffic demands will adversely effect delay (and operators’ costs)28 07/02/12
    29. 29. Conclusion  Scheduling is at the core of railway operations  Train plans which reduce the amount of delay per train improve the capacity and efficiency of the railway  Optimisation of train plans by application of the problem space search technique is much faster than manual techniques  Computer generation of train plans makes it possible to experiment with effects of train and infrastructure changes, and assess the usefulness of capital projects29 07/02/12

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