MocNet Simulation Specification

This document outlines the simulation to be developed in the MocNet project. It will be a discrete event simulation using next-event incrementing to advance time. As we're interested in cell-level data, we will simulate the movement between cells according to a probabilistic random walk. Despite this coarse discretisation of space, some underlying geographical features will be captured by the probability matrices. We note that even simulations that capture the geography more precisely will merge into our simulation when only returning cell-level data. The MocNet Simulation will also include some temporal dependencies caused by e.g. commuting. The simulation consists of two different parts: the mobility simulation and a call arrival simulation. Each part will be presented below. Also, two different geographical environments and three anomaly situations will be simulated: a road with an accident and a town centre with a flash mob and a flee situation

Optimisation of simultaneous train formation and car sorting at marshalling yards

Efficient and correct freight train marshalling is vital for high quality carload freight transportations. During marshalling, it is desirable that cars are sorted according to their individual drop-off locations in the outbound freight trains. Furthermore, practical limitations such as non-uniform and limited track lengths and the arrival and departure times of trains need to be considered. This paper presents a novel optimisation method for freight marshalling scheduling under these circumstances. The method is based on an integer programming formulation that is solved using column generation and branch and price. The approach minimises the number of extra shunting operations that have to be performed, and is evaluated on real-world data from the Hallsberg marshalling yard in Sweden

Evaluation of planning policies for marshalling track allocation using simulation

Planning the operational procedures in a railway marshalling yard is a complex problem. When a train arrives at a marshalling yard, it is uncoupled on an arrival yard and then its cars are rolled to a classification yard. All cars should eventually be rolled to the classification track that has been assigned to the train they’re supposed to depart with. However, there is normally not enough capacity to compound all trains at once. In Sweden, cars arriving before a track has been assigned to their train can be stored on separate tracks called mixing tracks. All cars on mixing tracks will be pulled back to the arrival yard, and then rolled to the classification yard again to allow for reclassification. Today all procedures are planned by experienced dispatchers, but there are no documented strategies or guidelines for efficient manual planning. The aim of this paper is to examine operational planning strategies that could help dispatchers find a feasible marshalling schedule that minimizes unnecessary mixing. In order to achieve this goal, two different online planning strategies have been tested using deterministic and stochastic simulation. The Hallsberg marshalling yard was used as a case study, and was simulated for the time period between December 2010 and May 2011. The first tested strategy simply assigns tracks to trains on a first come-first served basis, while the second strategy uses time limits to determine when tracks should be assigned to departing trains. The online planning algorithms have been compared with an offline optimized track allocation. The results from both the deterministic and the stochastic simulation show that the optimized allocation is better than all online strategies and that the second strategy with a time limit of 32 hours is the best online method

On the delivery robustness of train timetables with respect to production replanning possibilities

Measuring timetable robustness is a complex task. Previous efforts have mainly been focused on simulation studies or measurements of time supplements. However, these measurements don't capture the production flexibility of a timetable, which is essential for measuring the robustness with regard to the trains' commercial activity commitments, and also for merging the goals of robustness and efficiency. In this article we differentiate between production timetables and delivery timetables. A production timetable contains all stops, meetings and switch crossings, while a delivery timetable only contains stops for commercial activities. If a production timetable is constructed such that it can easily be replanned to cope with delays without breaking any commercial activity commitments it provides delivery robustness without compromising travel efficiency. Changing meeting locations is one of the replanning tools available during operation, and this paper presents a new framework for heuristically optimising a given production timetable with regard to the number of alternative meeting locations. Mixed integer programming is used to find two delivery feasible production solutions, one early and one late. The area between the two solutions represents alternative meeting locations and therefore also the replanning enabled robustness. A case study from Sweden demonstrates how the method can be used to develop better production timetables

Optimerad rangering: slutsatser och resultat från projektet RANPLAN

Sammanfattning Rapporten innehåller kortfattade slutsatser och resultat från en studie genomförd i projektet RANPLAN, som har utförts av SICS Swedish ICT AB på uppdrag av Trafikverket under åren 2010-2013. Fokus är på Hallsbergs rangerbangård, men resultaten är tillämpbara även på andra rangerbangårdar med vall. Datorkörningar visar att blanddragen kan öka kapaciteten på rangerbangårdar väsentligt, mätt i antalet samtidiga tåg som kan hanteras, till en kostnad av en ökad mängd vagnsrörelser. I en jämförande datorstudie av simulering och optimering framgick också att de optimala planerna var betydligt effektivare, mätt i antalet vagnsrörelser, än de simulerade planerna. Resultaten pekar tydligt på att datorstödd optimering av planeringsprocessen för rangerbangårdar både är praktiskt möjligt och kan ge stora effektivitetsvinster

Opportunities and challenges with new railway planning approach in Sweden

Long lead times in railway planning can give rise to a significant discrepancy between the original plan and the traffic eventually operated, resulting in inefficient utilization of capacity. Research shows that the railway sector in Sweden would benefit from a different planning approach in which capacity consuming decisions are pushed forward in time whenever possible. This approach is currently being implemented at Trafikverket, the Swedish Transport Administration. With it follows a number of mathematical opportunities and challenges, some of which will be presented in this paper

Optimized shunting with mixed-usage tracks

We consider the planning of railway freight classification at hump yards, where the problem involves the formation of departing freight train blocks from arriving trains subject to scheduling and capacity constraints. The hump yard layout considered consists of arrival tracks of sufficient length at an arrival yard, a hump, classification tracks of non-uniform and possibly non-sufficient length at a classification yard, and departure tracks of sufficient length. To increase yard capacity, freight cars arriving early can be stored temporarily on specific mixed-usage tracks. The entire hump yard planning process is covered in this paper, and heuristics for arrival and departure track assignment, as well as hump scheduling, have been included to provide the neccessary input data. However, the central problem considered is the classification track allocation problem. This problem has previously been modeled using direct mixed integer programming models, but this approach did not yield lower bounds of sufficient quality to prove optimality. Later attempts focused on a column generation approach based on branch-and-price that could solve problem instances of industrial size. Building upon the column generation approach we introduce a direct arc-based integer programming model, where the arcs are precedence relations between blocks on the same classification track. Further, the most promising models are adapted for rolling-horizon planning. We evaluate the methods on historical data from the Hallsberg shunting yard in Sweden. The results show that the new arc-based model performs as well as the column generation approach. It returns an optimal schedule within the execution time limit for all instances but from one, and executes as fast as the column generation approach. Further, the short execution times of the column generation approach and the arc-indexed model make them suitable for rolling-horizon planning, while the direct mixed integer program proved to be too slow for this. Extended analysis of the results shows that mixing was only required if the maximum number of concurrent trains on the classification yard exceeds 29 (there are 32 available tracks), and that after this point the number of extra car roll-ins increases heavily

Teknisk slutrapport för RANPLAN - Beräkningstöd för planering och resursallokering på rangerbangården

I denna rapport presenteras de modeller och resultat som projektet/RANPLAN-beräkningsstöd för planering och resursallokering/ producerat. RANPLAN finansierades av Trafikverkets FUD-program (F 09-11546/AL50) och pågick från januari 2010 till december 2011. Under projektets gång har ett flertal heuristiska algoritmer och optimeringmodeller tagits fram som skulle kunna förbättra och förenkla planeringen vid rangerbangårdar. En demonstrator baserad på historiska data visar att metoderna är så pass skalbara och effektiva att de är attraktiva för kommersiell implementering. Vidare presenteras förslag på lämpliga effektivitets- och kvalitetsmått för rangering

Slutrapport för Detaljering i tidtabellsplanering: mikro och makro (MIMA)

I dagens kapacitetstilldelningsprocess konstrueras en tidtabell i TrainPlan baserat på en datamodell som ligger på så kallad makro-nivå. Likaså är många av de optimeringsmetoder för tidtabellkonstruktion som tagits fram inom KAJT-projekt baserade på makro-modeller. Framtidens planeringssystem, TPS, har däremot en mer detaljerad datamodell, en modell på så kallad mikro-nivå. Målet med projektet MIMA var att undersöka och kartlägga vilka olika sorters detaljeringsnivåer som behövs och finns inom Trafikverkets planeringsverksamhet. Projektet fokuserade särskilt på (1) vilken detaljeringsgrad som efterfrågas i olika delar av planeringsprocessen och (2) hur detaljeringsgraden påverkar möjligheterna för framtida stödsystem med automatisk tidtabellsgenerering. Resultaten av ett flertal intervjuer och studier av forskningspublikationer och annan teknisk dokumentation visar att det finns flera olika datamodeller inom Trafikverket och att dessa inte alltid är kompatibla med varandra. Det finns också behov på Trafikverket av att kunna planera på både mikro- och makro-nivå. Förenklat kan man säga att om planeringen ska gå snabbt och kunna hantera större ändringar krävs en makro-modell, men om t.ex. påverkan av små infrastrukturförändringar ska analyseras är en mikro-modell nödvändig. När det kommer till möjligheterna för framtida stödsystem med automatisk tidtabellsgenerering så är de flesta modeller som utvecklats makro-modeller. Det finns dock vetenskapliga publikationer som presenterar metoder för att iterativt anpassa en makro-lösning så att den blir kompatibel även med en mikro-modell, samt för hur man kan konstruera en makro-modell som ger lösningar som är kompatibla med en underliggande mikro-modell. En intressant iakttagelse är att mikro-modeller företrädelsevis används vid strategisk planering och utbildning, medan man i operativ drift använder grövre modeller (undantaget EBICOS Trafikbilder). Detta väcker frågeställningar om vilken information det egentligen är som fjärrtågklarerare har behov av i det operativa skedet, och om tidtabellsprocessen är anpassat för att ta fram denna. Vi har i MIMA inte haft möjlighetatt intervjua driftledningspersonal, och detta är således en viktig uppgift för framtiden. Likaså vore det värdefullt om Trafikverket skapade en enad modellflora med både mikrooch makro-modeller för planering

Optimisation models for train timetabling and marshalling yard planning

Railways provide high capacity, safe and energy efficient transportation of goods and passengers. However, railway transportation also suffers from intrinsic restrictions and the effectiveness and efficiency of the transportation depend on the railway actors’ ability to solve a set of hard and interconnected planning problems. As the digitalisation of rail-way planning advance, compute-intensive decision support tools could be implemented to support the planners’ work. Two support functions that would be useful are automatic generation of new plans and optimisation of existing plans. In this thesis, mathematical models are developed and analysed for optimisation of (1) train timetables and (2) marshalling yard plans. The aim is to investigate the feasibility and potential of using mixed integer linear programming (MILP) models to solve these two planning problems. To this aim, requirements and planning goals are identified and modelled as mathematical constraints and objective functions. The resulting mathematical models are then tested on realistic problem instances, and the execution times and optimised plans are analysed to determine if the mathematical models could be useful in practice. The thesis contributes with an analysis of the definition of ”good” in a railway timetable setting from the perspective of an infrastructure manager, a novel mathematical model for timetable planning, an optimisation-based heuristic for decreasing execution times and last but not least an analysis of the potential of using optimisation to enable a new type of annual capacity allocation. For marshalling yard planning, the thesis contributes with an analysis of three different mathematical models for planning one of the sub-yards of a marshalling yard, and with an extended, more comprehensive, mathematical model that can be used to plan two sub-yards. Further, a heuristic is developed for the more comprehensive problem, and the effects of optimising two sub-yards rather than one are analysed. The overall conclusion is that MILP models can contribute to improved railway planning. By using MILP optimisation, more effective plans can be made faster. However, more research is needed to reach the full potential of mathematical optimisation for railway planning problems, in particular when it comes to user experience and user interaction, but also to further decrease the execution times and extend the problem scope that can be handled. This thesis consists of two parts. The first part introduces and summarises the research. It provides background knowledge on the two planning problems as well as on mathematical optimisation, and also present the research framework and some overall conclusions and suggestions for future work. The second part of the thesis consists of five appended papers, three on train timetabling and two on marshalling yard planning