Instituto Universitario de Automática e Informática Industrial, Universidad Politécnica de Valencia, 46022 Valencia, Spain
Academic Editor: J. Jiang
Copyright © 2009 Miguel A. Salido and Federico Barber. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Train scheduling has been a significant issue in the railway industry. Over
the last few years, numerous approaches and tools have been developed to
compute railway scheduling. In this paper, we present a set of heuristics
for a constraint-based train scheduling tool, which is a project in collaboration
with the National Network of Spanish Railways (RENFE), Spain.
We formulate train scheduling as constraint optimization problems. Three
heuristics are developed to speed up and direct the search toward suboptimal
solutions in periodic train scheduling problems. The feasibility of
our problem-oriented heuristics is confirmed with experimentation using
real-life data. The results show that these techniques enable MIP solvers
such as LINGO and ILOG Concert Technology (CPLEX) to terminate
earlier with good solutions.