ONTIME is equipped with powerful optimisers capable of obtaining optimised solutions for different kinds of scheduling problems

• Long-term scheduling
Equipped with three optimisers:
(1) performs line planning, which obtains a set of service lines (train routes with corresponding train hour frequency) that satisfy a given passenger demand taking into consideration fleet size constraints;
(2) obtains periodic timetables (e.g. timetables that repeat themselves over a fixed period of time) based on the service lines produced with the previous optimiser;
(3) obtains non-periodic timetables for metro systems, which support simple linear, circular, Y shaped, and X shaped lines, and other configurations where different types of services have to run on the same physical tracks

ONTIME optimisers obtain solutions that optimise several goals at the same time. Popular, but sometimes conflicting goals are:

• Long-term scheduling
In line planning, maximise revenue (according to the covered passenger demand), minimise operational costs (track slot allocation and vehicle usage cost), and maximise passenger satisfaction (e.g. reach final destination with minimum amount of transfers); in periodic timetables, minimise the overall passenger travel time which includes synchronizing arrivals and departures of connecting trains; in non-periodic timetables, making sure that transitions between different train hour frequencies do not have a fluctuating behavior

ONTIME optimisers use state-of-the-art technology.
In the line planning optimiser, the techniques used are genetic algorithms, dynamic programming and other metaheuristics.
In the periodic timetable optimiser, the techniques used are modulo network simplex, integer linear programming, constraint programming, and greedy algorithms.
In the non-periodic timetables optimiser, a heuristic algorithm is used to perform the transitions of different timetable patterns obtained with a periodic timetable generation algorithm.