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dc.contributor.authorAkgun, Ozgur
dc.contributor.authorGent, Ian Philip
dc.contributor.authorJefferson, Christopher Anthony
dc.contributor.authorMiguel, Ian James
dc.contributor.authorNightingale, Peter William
dc.contributor.authorSalamon, András Z.
dc.contributor.editorHooker, John
dc.date.accessioned2018-08-28T14:30:08Z
dc.date.available2018-08-28T14:30:08Z
dc.date.issued2018
dc.identifier.citationAkgun , O , Gent , I P , Jefferson , C A , Miguel , I J , Nightingale , P W & Salamon , A Z 2018 , Automatic discovery and exploitation of promising subproblems for tabulation . in J Hooker (ed.) , Principles and Practice of Constraint Programming : 24th International Conference, CP 2018, Lille, France, August 27-31, 2018, Proceedings . Lecture Notes in Computer Science , vol. 11008 , Springer , pp. 3-12 , 24th International Conference on Principles and Practice of Constraint Programming (CP 2018) , Lille , France , 27/08/18 . https://doi.org/10.1007/978-3-319-98334-9_1en
dc.identifier.citationconferenceen
dc.identifier.isbn9783319983332
dc.identifier.isbn9783319983349
dc.identifier.issn0302-9743
dc.identifier.otherPURE: 253604678
dc.identifier.otherPURE UUID: b170a1ed-fb03-483a-860a-1e1482829944
dc.identifier.otherScopus: 85053156483
dc.identifier.otherORCID: /0000-0002-5052-8634/work/47928954
dc.identifier.otherORCID: /0000-0001-9519-938X/work/47928989
dc.identifier.otherORCID: /0000-0002-1415-9712/work/47929008
dc.identifier.otherORCID: /0000-0003-2979-5989/work/60887576
dc.identifier.otherORCID: /0000-0002-6930-2686/work/68281469
dc.identifier.otherWOS: 000546520500001
dc.identifier.urihttp://hdl.handle.net/10023/15892
dc.descriptionFunding: EP/P015638/1 and EP/P026842/1. Dr Jefferson holds a Royal Society University Research Fellowship.en
dc.description.abstractThe performance of a constraint model can often be improved by converting a subproblem into a single table constraint. In this paper we study heuristics for identifying promising subproblems. We propose a small set of heuristics to identify common cases such as expressions that will propagate weakly. The process of discovering promising subproblems and tabulating them is entirely automated in the tool Savile Row. A cache is implemented to avoid tabulating equivalent subproblems many times. We give a simple algorithm to generate table constraints directly from a constraint expression in Savile Row. We demonstrate good performance on the benchmark problems used in earlier work on tabulation, and also for several new problem classes.
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofPrinciples and Practice of Constraint Programmingen
dc.relation.ispartofseriesLecture Notes in Computer Scienceen
dc.rights© 2018, Springer Nature Switzerland AG. This work has been made available online in accordance with the publisher’s policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1007/978-3-319-98334-9_1en
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectDASen
dc.subject.lccQA75en
dc.titleAutomatic discovery and exploitation of promising subproblems for tabulationen
dc.typeConference itemen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews.School of Computer Scienceen
dc.contributor.institutionUniversity of St Andrews.Centre for Interdisciplinary Research in Computational Algebraen
dc.identifier.doihttps://doi.org/10.1007/978-3-319-98334-9_1


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