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In this paper we study a general formulation of the train platforming problem, which contains as special cases all the versions previously considered in the literature as well as a case study from the Italian Infrastructure manager that we addressed. In particular, motivated by our case study, we consider a general quadratic objective function, and propose a new way to linearize it by using a small number of new variables along with a set of constraints that can be separated efficiently by solving an appropriate linear program. The resulting integer linear programming formulation has a continuous relaxation that leads to strong bounds on the optimal value. For the instances in our case study, we show that a simple diving heuristic based on this relaxation produces solutions that are much better than those produced by a simple heuristic currently in use, and that often turn out to be (nearly-) optimal.
@InProceedings{caprara_et_al:OASIcs.ATMOS.2007.1174,
author = {Caprara, Alberto and Galli, Laura and Toth, Paolo},
title = {{04. Solution of the Train Platforming Problem}},
booktitle = {7th Workshop on Algorithmic Approaches for Transportation Modeling, Optimization, and Systems (ATMOS'07)},
pages = {49--61},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-939897-04-0},
ISSN = {2190-6807},
year = {2007},
volume = {7},
editor = {Ahuja, Ravindra K. and Liebchen, Christian and Mesa, Juan A.},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2007.1174},
URN = {urn:nbn:de:0030-drops-11741},
doi = {10.4230/OASIcs.ATMOS.2007.1174},
annote = {Keywords: Train Platforming, Train Routing, Branch-and-Cut-and-Price, Quadratic Objective Function, Linearization}
}