Context and challenge
Rail networks run at high utilization, which means even small planned maintenance can have cascading effects. When capacity is reduced, planners must reshape train movements, resolve conflicts, and ensure the result remains safe and executable. Traditionally, this process is manual, labor-intensive, and heavily dependent on expert judgment.
At the same time, the planning environment is becoming more demanding. Timetables increasingly need to be prepared earlier and with greater consistency, while maintenance and operational constraints remain unavoidable. The result is a complex planning challenge that is both labor-intensive and difficult to scale using purely manual methods.
Lynxx solution
RAAD recommends the most effective adjustments to the base timetable, focusing on maintaining feasibility while minimizing deviation from the original schedule. The underlying mathematical model proposes alternative timetables that balance available capacity across passenger, international, and freight services. It ensures safety constraints are respected, passenger inconvenience is limited, and operational feasibility is maintained across the network.
The same modeling approach can also support other complex scenarios beyond maintenance disruptions. It can incorporate changes in rail operator schedules, account for limitations related to personnel availability, and adapt timetables to infrastructure constraints such as bridge openings. This flexibility makes RAAD a robust tool for real-world planning, where constraints rarely appear in isolation.
Advanced innovation
The scale and complexity of the problem made it impractical to capture every requirement within a single optimization model. Lynxx therefore decomposed the challenge into two interdependent models that work together in a feedback loop.
The first model focuses on network feasibility by checking whether train flows between stations remain possible under reduced capacity while respecting safety rules and timing constraints. The second model addresses station feasibility by ensuring workable track assignments and local operational constraints at stations. By iterating between these two perspectives, RAAD produces an alternative timetable that is both network-feasible and station-feasible, while remaining efficient and practical to compute.
Results & impact
RAAD significantly reduces the workload required to produce alternative timetables, allowing planning teams to focus more on decision-making and less on manual conflict resolution. It also increases the consistency of timetable proposals by reducing the influence of individual preferences and subjective judgment, which helps create more predictable planning outcomes across scenarios.
By supporting earlier availability of feasible timetables, the solution improves the ability of rail organizations to plan ahead and respond faster to disruptions. This strengthens rail’s competitiveness as a mode of transport and supports better preparation for passengers and operators alike.
Strategic significance
This project reflects Lynxx’s core capabilities in translating complex real-world operational challenges into precise mathematical models and applying data science and operations research to deliver measurable impact. It also demonstrates how advanced optimization can contribute to more sustainable mobility by helping rail systems make smarter use of existing infrastructure, even under constrained conditions.
