Train timetables and track maintenance

Rail networks need regular, scheduled maintenance in
order to operate efficiently. However,
maintenance needs to be carefully coordinated with
train operations, as the cost of restricting
the train schedule potentially results in significant
lost revenues for railways. Traditional
methods of constructing train timetables with
allowance for track maintenance take several weeks,
allowing little opportunity to explore potential
improvements. This book presents new mathematical
techniques for producing integrated train timetables
and track maintenance schedules so that, when
evaluated according to certain key performance
indicators, the overall schedule is the best
possible. The research is directed at sparse long
haul rail systems. The techniques in this book
include a new probabilistic method that can quickly
generate a range of different feasible
integrated schedules. The speed of the method allows
it to be used in a operational setting, both
to create schedules and to test different scenarios.
Rail operators, mathematicians and engineers
may gain useful insight from this book to aid their
development of operationally efficient methods
for railway management.

Autorentext

Amie Albrecht is a graduate of the University of South Australia
(UniSA), with a PhD in Industrial and Applied Mathematics. She
works as a researcher at UniSA on scheduling and control problems.

Klappentext

Rail networks need regular, scheduled maintenance in
order to operate efficiently. However,
maintenance needs to be carefully coordinated with
train operations, as the cost of restricting
the train schedule potentially results in significant
lost revenues for railways. Traditional
methods of constructing train timetables with
allowance for track maintenance take several weeks,
allowing little opportunity to explore potential
improvements. This book presents new mathematical
techniques for producing integrated train timetables
and track maintenance schedules so that, when
evaluated according to certain key performance
indicators, the overall schedule is the best
possible. The research is directed at sparse long
haul rail systems. The techniques in this book
include a new probabilistic method that can quickly
generate a range of different feasible
integrated schedules. The speed of the method allows
it to be used in a operational setting, both
to create schedules and to test different scenarios.
Rail operators, mathematicians and engineers
may gain useful insight from this book to aid their
development of operationally efficient methods
for railway management.