This paper describes an optimization
framework for rolling stock ros tering and maintenance
scheduling at a busy workshop. A new mixed- integer linearprogramming
formulation is provided for the maintenance
scheduling problem faced by Trenitalia (train operating
company) man agers, with input data taken from the rolling
stock rostering plan. The computational results are carried
out on a Trenitalia’s maintenance site located in Naples.
The solutions computed via a commercial MILP solver are
compared with practical solutions. A relevant cost reduction
is pos sible by using the proposed framework, involving
both rostering and maintenance scheduling. We also show
how the proposed method can be used as an effective tool
to absorb real-time timetable perturbations while respecting
the agreed level of service.
- Gennaio