Rail Capacity Modelling with Constraint Programming

We describe a constraint programming approach to establish the coal carrying capacity of a large (2,670 km) rail network in north-eastern Australia. Computing the capacity of such a network is necessary to inform infrastructure planning and investment decisions but creating a useful model of rail op...

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Bibliographic Details
Published inIntegration of AI and OR Techniques in Constraint Programming Vol. 9676; pp. 170 - 186
Main Authors Harabor, Daniel, Stuckey, Peter J.
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 01.01.2016
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Constraint Programming
Headway Time
Mathematical theory of computation
Rail Network
Rail System
Rolling Stock
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Summary:We describe a constraint programming approach to establish the coal carrying capacity of a large (2,670 km) rail network in north-eastern Australia. Computing the capacity of such a network is necessary to inform infrastructure planning and investment decisions but creating a useful model of rail operations is challenging. Analytic approaches exist but they are not very accurate. Simulation methods are common but also complex and brittle. We present an alternative where rail capacity is computed using a constraint-based optimisation model. Developed entirely in MiniZinc, our model not only captures all dynamics of interest but is also easily extended to explore a wide range of possible operational and infrastructural changes. We give results from a number of such case studies and compare against an industry-standard analytic approach.
ISBN:3319339532
9783319339535
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-33954-2_13