Abstract
Train dispatching is vital for the punctuality of train services, which is critical for
a train operating company (TOC) to maintain its competitiveness. Due to the introduction
of competition in the railway transport market, the issue of discrimination is
attracting more and more attention. This paper focuses on delivering non-discriminatory
train dispatching solutions while multiple TOCs are competing in a rail transport
market, and investigating impacting factors of the inequity of train dispatching
solutions. A mixed integer linear programming (MILP) model is first proposed, in which
the inequity of competitors (i.e., trains and TOCs) is formalized by a set of
constraints. In order to provide a more flexible framework, a model is further
reformulated where the inequity of competitors is formalized as the maximum individual
deviation of competitors’ delay cost from average delay cost in the objective function.
Complex infrastructure capacity constraints are considered and modelled through a big
M-based approach. The proposed models are solved by a standard MILP solver. A set of
comprehensive experiments is conducted on a real-world dataset adapted from the Dutch
railway network to test the efficiency, effectiveness, and applicability of the proposed
models, as well as determine the trade-off between train delays and delay equity.
Keywords
Train dispatching,
EquityTrain Operating Company (TOC),
Mixed-integer linear programming
Highlights
• We propose a methodology for delivering non-discriminatory train dispatching solutions.
•
We formulate the non-discriminatory train dispatching problem as mixed integer linear programming models.
•
We formalize equity of train delays by soft objective function or hard constraints.
•
Our methodology provides support for managing railway traffic in a non-discriminatory manner.
原文传递： https:/www.sciencedirect.com/science/article/pii/S0968090X17301225
