Skip to content

Research at St Andrews

Automatic generation and selection of streamlined constraint models via Monte Carlo search on a model lattice

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Streamlined constraint reasoning is the addition of uninferred constraints to a constraint model to reduce the search space, while retaining at least one solution. Previously it has been established that it is possible to generate streamliners automatically from abstract constraint specifications in Essence and that effective combinations of streamliners can allow instances of much larger scale to be solved. A shortcoming of the previous approach was the crude exploration of the power set of all combinations using depth and breadth first search. We present a new approach based on Monte Carlo search over the lattice of streamlined models, which efficiently identifies effective streamliner combinations.
Close

Details

Original languageEnglish
Title of host publicationPrinciples and Practice of Constraint Programming
Subtitle of host publication24th International Conference, CP 2018, Lille, France, August 27-31, 2018, Proceedings
EditorsJohn Hooker
Place of PublicationCham
PublisherSpringer
Pages362-372
ISBN (Electronic)9783319983349
ISBN (Print)9783319983332
DOIs
Publication statusPublished - 2018

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume11008
ISSN (Print)0302-9743

Discover related content
Find related publications, people, projects and more using interactive charts.

View graph of relations

Related by author

  1. Cloud benchmarking for maximising performance of scientific applications

    Varghese, B., Akgun, O., Miguel, I. J., Thai, L. T. & Barker, A. D., 1 Jan 2019, In : IEEE Transactions on Cloud Computing. 7, 1, p. 170-182 13 p., 7553491.

    Research output: Contribution to journalArticle

  2. Closed frequent itemset mining with arbitrary side constraints

    Kocak, G., Akgun, O., Miguel, I. J. & Nightingale, P. W., 17 Nov 2018, 2018 IEEE International Conference on Data Mining Workshops (ICDMW). Tong, H., Li, Z. J., Zhu, F. & Yu, J. (eds.). IEEE Computer Society, p. 1224 - 1232 9 p. 8637581

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  3. Modelling Langford's Problem: a viewpoint for search

    Akgün, Ö. & Miguel, I., 27 Aug 2018, The Seventeenth Workshop on Constraint Modelling and Reformulation (ModRef 2018), Proceedings. 11 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  4. A framework for constraint based local search using ESSENCE

    Akgun, O., Attieh, S. W. A., Gent, I. P., Jefferson, C. A., Miguel, I. J., Nightingale, P. W., Salamon, A. Z., Spracklen, P. & Wetter, J. P., 13 Jul 2018, Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. Lang, J. (ed.). International Joint Conferences on Artificial Intelligence, p. 1242-1248 7 p.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  5. Metamorphic testing of constraint solvers

    Akgun, O., Gent, I. P., Jefferson, C. A., Miguel, I. J. & Nightingale, P. W., 2018, Principles and Practice of Constraint Programming: 24th International Conference, CP 2018, Lille, France, August 27-31, 2018, Proceedings. Hooker, J. (ed.). Springer, p. 727-736 (Lecture Notes in Computer Science; vol. 11008).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

ID: 255103139