@inbook{05eef16f4b59478fbe5a4d725d3e74ec,
title = "Large neighbourhood search for energy-efficient train timetabling",
abstract = "The electric rail sector, like many sectors, is looking for means to reduce its energy consumption and energy cost. In this work we consider the scenario where the utility provider charges based on the maximum consumption over a period. Therefore one wishes to schedule the departure of trains such that the aggregate load is balanced across time periods while satisfying timetabling and resource restrictions. We present an approach which combines the strengths of a number of research areas such as constraint programming, linear programming, mixed-integer programming, and large neighbourhood search. The empirical performance on instances from an ongoing research challenge demonstrates the approach's ability to dramatically reduce the overall energy cost. In addition, we are able to close a number of the instances for which we prove optimality.",
keywords = "Constraint programming, Energy efficiency, Large neighbourhood search, Mixed-integer programming, Optimisation, Timetabling",
author = "Diarmuid Grimes and Barry Hurley and Deepak Mehta and Barry O'Sullivan",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 27th IEEE International Conference on Tools with Artificial Intelligence, ICTAI 2015 ; Conference date: 09-11-2015 Through 11-11-2015",
year = "2016",
month = jan,
day = "4",
doi = "10.1109/ICTAI.2015.122",
language = "English",
series = "Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI",
publisher = "IEEE Computer Society",
pages = "828--835",
booktitle = "Proceedings - 2015 IEEE 27th International Conference on Tools with Artificial Intelligence, ICTAI 2015",
address = "United States",
}
