Rail Transportation Network Optimization and Planning with Simulation Software

Rail Transportation Network Optimization and Planning with Simulation Software

Netherlands Railways is the main passenger railway operator in the Netherlands and one of the busiest rail networks in the world after Switzerland. Every year, 9 million people travel on blue and yellow trains. The railways run ‘from Utrecht to Tibet’ and spread out for 6,830 kilometers.

This case study highlights, in total, 5 railway optimization and planning projects that were successfully implemented with AnyLogic simulation software:

  1. Rail network planning to prepare for disruptions and innovations
  2. Railway optimization to increase train frequency
  3. Train procurement planning
  4. Testing passenger behavior during train boarding
  5. Railway transportation network design for new repair stations

Case study 1: Rail transportation network planning – preparing for disruptions


In this project, Netherlands Railways engineers tested innovations using simulation modeling because they could not try out many railway innovations in real life. Also, they could not cause disruptions on railway lines because it would destroy the entire rail transportation system.

Netherlands Railways engineers needed to test the procurement and introduction of the new rolling stock and innovations such as self-driving trains and the digital train protection system.

Netherlands Railways previously used only microscopic, very detailed simulations, but they were hard to work with.

Disruptions are one of the main problems for Netherlands Railways. They are hard to predict, but happen every day.

There was no day when all trains were on time with the right crew and the right rolling stock. Disruptions could be cows on the track, doors not closing, or power failures. For example, a high-voltage cable dropped on the railway track, and it took half a year to repair it. Usually, they simplified problems into the following: a broken train blocked the track, or the track was blocked and no trains were allowed to pass.


Using AnyLogic simulation software, they developed a macroscopic, conceptual railway planning tool. Engineers could develop a concept rapidly, spending less than one week on a new model. They integrated AnyLogic with a lot of other predictive analytics tools. The tool was interactive and easy to use for the end users.

The AnyLogic simulation model was much better than the visualization of the railway network that was previously used by Netherlands Railways. The model simulated all the trains for the whole day.

The team modeled one line from the rail network that they were interested in. Then they loaded a timetable from any year, past or future, e.g., 2030. They simplified this data into bits of infrastructure, stations, platforms, and trains.

The model developers loaded real data from 2019 and fitted it into stochastic distributions. The AnyLogic model was used to predict the probability that a train would be on time and simulate the flow of trains.

Schematic track layout used for railway optimization and planning

Schematic track layout used for railway optimization and planning

Netherlands Railways developers built a simulation model to predict the network-wide punctuality that could not be done by hand. The AnyLogic model provided realistic breakdown rates for trains and infrastructure. Netherlands Railways developers used some simple rescheduling rules.

Macroscopic railway layout in the simulation-based railway planning tool

Macroscopic railway layout (click to enlarge)

In case of an incident, passengers who were not in the affected zone could continue to be transported. It was important to limit the disruption to as small an area as possible and to turn trains at the edges to keep passengers on time.

Moreover, Netherlands Railways developers ran a Monte Carlo experiment. In the model, there were 10 stochastic distributions. Every time the train was departing, it showed possible delays or failures. It was connected to the SQL database to load parameter sets that were predefined.

Railway modeling and planning results

The engineers were able to test certain kinds of disruptions. When an experiment was run, the developers got the KPIs, that were the total delays of the trains, the number of failures, cancelled trains, and punctuality. The running time of the model was quite good, as this experiment showed the results for 5 years in around 5 minutes of running it.

Monte Carlo experiment in the simulation-based railway planning tool

Monte Carlo experiment in the simulation-based railway planning tool (click to enlarge)

Netherlands Railways has been using the simulation-based railway planning tool for almost 5 years. During this time, they made some changes to it. For instance, they used actions more in the transition instead of the state entry. It prevented confusion when using historical states.

Previously, Netherlands Railways engineers drew the model layout by hand, gave it a name, and connected it to an input file, but then they started to make automatization with the use of AnyLogic templates that enabled them to switch easily between layouts (parts of the Netherlands). Thanks to AnyLogic software, it became possible to model almost the whole of the Netherlands rail transportation network.

To get inputs from the timetable planning software and the rolling stock scheduler, the model was connected to some of their production systems. Netherlands Railways used XML files, converted them to a SQL database, and then AnyLogic got the input data from SQL. After the simulation, the output data could be exported from AnyLogic to an SQL database and visualized with Power BI.

Case study 2: Railway optimization to increase train frequency


Furthermore, Netherlands Railways were asked by the government to increase the frequency of the trains while maintaining the same KPI, which was punctuality level. A busy network always decreased punctuality because there were more trains that could fail, more passengers that could cause delays, and the infrastructure was more heavily utilized.


Netherlands Railways needed to investigate how to optimize their transportation network to maintain the same high level of punctuality. For this purpose, they used a very abstract model. It included a number of slow and fast trains, tracks, stations, and the real timetable. They simulated different timetables.


The picture below illustrates the percentage of punctual trains that show a performance drop. For example, the orange bar shows four fast trains per hour without building the new tracks. If they added two tracks to the infrastructure, the level of punctuality would be higher.

Percentage of punctual trains in the transportation network optimization model

Percentage of punctual trains

One of their challenges was how to drive more trains with the same infrastructure. This performance drop could be compensated not only by infrastructure but also by train reliability and timetable adaptability.

Case study 3: Train procurement planning


Netherlands Railways wanted to buy the double-deck motor units that required extra investment. The double-deck rolling stock was the most capital-intensive asset, so they needed to find out if this investment in reliability was worth the money.


They simulated a new timetable for 2040 where the frequency would be doubled – around 8 or 10 trains on a track per hour. The model considered the mixed environment with all train types, failure data from 2019, and failure rates of the new trains.


Trains arrival times were one of the KPIs. The customer benefit was punctuality.

The difference in train punctuality for reliability of new trains

The difference in train punctuality for reliability of new trains

If the reliability of new trains was improved by 20%, only 0,08% of modeled trains would arrive on time. The AnyLogic simulation model showed that it was not cost-effective. Thus, Netherlands Railways decided to invest in better incident management.

Other projects: Testing passenger behavior and designing a railway transportation network

In addition, the engineers tested how passenger behavior would change and affect the boarding process if they used one-side boarding trains. They also designed the entire railway transportation network to identify the optimal locations for repair stations.

Among the results that Netherlands Railways achieved with the use of AnyLogic as a railway planning software were the introduction of new rolling stock, the new safety system, automated railway operations, long-term transportation network infrastructure investment, and short-term operational decisions.

The case studies were presented by Camiel Simons, of Netherlands Railways, at the AnyLogic Conference 2022.

The slides are available as a PDF.

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