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Rescheduling of light rail trains during disruption : an optimization model for Bybanen in Bergen

Lie, Sturla; Sinnes, Jonathan
Master thesis
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URI
https://hdl.handle.net/11250/2648850
Date
2019
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  • Master Thesis [3258]
Abstract
When a disruption occurs in an urban rail system, it usually results in significant disturbances

due to limited operational flexibility. In this thesis, we develop an optimization model that

efficiently reschedules trains during partial blockage on a double-tracked light rail line. The

rescheduled timetable is obtained by a mixed-integer linear programming model that minimizes

the sum of delay at all stations by rescheduling trains through the opposite track using

crossovers.

The numerical analyses are performed on three case studies based on real-world data from

Bybanen light rail system in the city of Bergen. Our findings suggest that the proposed

optimization model can safely reschedule train operations through crossovers located at their

actual position in the network. Our findings also indicate that when minimizing delay at all

stations instead of at the final stations, it contributes to more evenly distribution of passenger

delay. This is demonstrated by comparing two different objective functions.

The results furthermore imply that by increasing frequencies, a crossover strategy will be

harder to implement following larger density of trains. Changing from manual to automatic

crossovers seems to have little effect on rescheduling of train operations. When expanding to

double-tracked crossovers, however, the results indicate that punctuality and train operations

are significantly improved. Finally, as the optimization model solves the most comprehensive

case study in six seconds, the model can be applied by dispatchers in real-time decisions.

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