Rail capacity modelling with constraint programming

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

We describe a constraint programming approach to establish the coal carrying capacity of a large (2,670 km) rail network in northeastern 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.

Original languageEnglish
Title of host publicationIntegration of AI and OR Techniques in Constraint Programming
Subtitle of host publication13th International Conference, CPAIOR 2016 Banff, AB, Canada, May 29 – June 1, 2016 Proceedings
EditorsClaude-Guy Quimper
Place of PublicationCham Switzerland
PublisherSpringer
Pages170-186
Number of pages17
ISBN (Electronic)9783319339542
ISBN (Print)9783319339535
DOIs
Publication statusPublished - 2016
Externally publishedYes
EventInternational Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming for Combinatorial Optimization Problems 2016 - Banff AB, Canada
Duration: 29 May 20161 Jun 2016
Conference number: 13th
https://symposia.cirrelt.ca/CPAIOR2016/en/home

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume9676
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming for Combinatorial Optimization Problems 2016
Abbreviated titleCPAIOR 2016
CountryCanada
CityBanff AB
Period29/05/161/06/16
Internet address

Cite this

Harabor, D., & Stuckey, P. J. (2016). Rail capacity modelling with constraint programming. In C-G. Quimper (Ed.), Integration of AI and OR Techniques in Constraint Programming : 13th International Conference, CPAIOR 2016 Banff, AB, Canada, May 29 – June 1, 2016 Proceedings (pp. 170-186). (Lecture Notes in Computer Science ; Vol. 9676). Cham Switzerland: Springer. https://doi.org/10.1007/978-3-319-33954-2_13
Harabor, Daniel ; Stuckey, Peter J. / Rail capacity modelling with constraint programming. Integration of AI and OR Techniques in Constraint Programming : 13th International Conference, CPAIOR 2016 Banff, AB, Canada, May 29 – June 1, 2016 Proceedings. editor / Claude-Guy Quimper. Cham Switzerland : Springer, 2016. pp. 170-186 (Lecture Notes in Computer Science ).
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Harabor, D & Stuckey, PJ 2016, Rail capacity modelling with constraint programming. in C-G Quimper (ed.), Integration of AI and OR Techniques in Constraint Programming : 13th International Conference, CPAIOR 2016 Banff, AB, Canada, May 29 – June 1, 2016 Proceedings. Lecture Notes in Computer Science , vol. 9676, Springer, Cham Switzerland, pp. 170-186, International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming for Combinatorial Optimization Problems 2016, Banff AB, Canada, 29/05/16. https://doi.org/10.1007/978-3-319-33954-2_13

Rail capacity modelling with constraint programming. / Harabor, Daniel; Stuckey, Peter J.

Integration of AI and OR Techniques in Constraint Programming : 13th International Conference, CPAIOR 2016 Banff, AB, Canada, May 29 – June 1, 2016 Proceedings. ed. / Claude-Guy Quimper. Cham Switzerland : Springer, 2016. p. 170-186 (Lecture Notes in Computer Science ; Vol. 9676).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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AB - We describe a constraint programming approach to establish the coal carrying capacity of a large (2,670 km) rail network in northeastern 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.

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Harabor D, Stuckey PJ. Rail capacity modelling with constraint programming. In Quimper C-G, editor, Integration of AI and OR Techniques in Constraint Programming : 13th International Conference, CPAIOR 2016 Banff, AB, Canada, May 29 – June 1, 2016 Proceedings. Cham Switzerland: Springer. 2016. p. 170-186. (Lecture Notes in Computer Science ). https://doi.org/10.1007/978-3-319-33954-2_13