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Automatically improving constraint models in Savile Row
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dc.contributor.author | Nightingale, Peter | |
dc.contributor.author | Akgün, Özgür | |
dc.contributor.author | Gent, Ian P. | |
dc.contributor.author | Jefferson, Christopher | |
dc.contributor.author | Miguel, Ian | |
dc.contributor.author | Spracklen, Patrick | |
dc.date.accessioned | 2018-07-12T23:34:16Z | |
dc.date.available | 2018-07-12T23:34:16Z | |
dc.date.issued | 2017-10 | |
dc.identifier | 250522992 | |
dc.identifier | 8a56ff34-e5bc-4dad-a3bc-c63d391de55e | |
dc.identifier | 85025834662 | |
dc.identifier | 000411167600002 | |
dc.identifier.citation | Nightingale , P , Akgün , Ö , Gent , I P , Jefferson , C , Miguel , I & Spracklen , P 2017 , ' Automatically improving constraint models in Savile Row ' , Artificial Intelligence , vol. 251 , pp. 35-61 . https://doi.org/10.1016/j.artint.2017.07.001 | en |
dc.identifier.issn | 0004-3702 | |
dc.identifier.other | RIS: urn:7B45A791D32409E8AD08829360479802 | |
dc.identifier.other | ORCID: /0000-0002-5052-8634/work/35084050 | |
dc.identifier.other | ORCID: /0000-0001-9519-938X/work/35084065 | |
dc.identifier.other | ORCID: /0000-0003-2979-5989/work/60887533 | |
dc.identifier.other | ORCID: /0000-0002-6930-2686/work/68281427 | |
dc.identifier.uri | https://hdl.handle.net/10023/15338 | |
dc.description | Authors thank the EPSRC for funding this work through grants EP/H004092/1, EP/K015745/1, EP/M003728/1, and EP/P015638/1. In addition, Dr Jefferson is funded by a Royal Society University Research Fellowship. | en |
dc.description.abstract | When solving a combinatorial problem using Constraint Programming (CP) or Satisfiability (SAT), modelling and formulation are vital and difficult tasks. Even an expert human may explore many alternatives in modelling a single problem. We make a number of contributions in the automated modelling and reformulation of constraint models. We study a range of automated reformulation techniques, finding combinations of techniques which perform particularly well together. We introduce and describe in detail a new algorithm, X-CSE, to perform Associative-Commutative Common Subexpression Elimination (AC-CSE) in constraint problems, significantly improving existing CSE techniques for associative and commutative operators such as +. We demonstrate that these reformulation techniques can be integrated in a single automated constraint modelling tool, called Savile Row, whose architecture we describe. We use Savile Row as an experimental testbed to evaluate each reformulation on a set of 50 problem classes, with 596 instances in total. Our recommended reformulations are well worthwhile even including overheads, especially on harder instances where solver time dominates. With a SAT solver we observed a geometric mean of 2.15 times speedup compared to a straightforward tailored model without recommended reformulations. Using a CP solver, we obtained a geometric mean of 5.96 times speedup for instances taking over 10 seconds to solve. | |
dc.format.extent | 27 | |
dc.format.extent | 767378 | |
dc.language.iso | eng | |
dc.relation.ispartof | Artificial Intelligence | en |
dc.subject | Constraint satisfaction | en |
dc.subject | Common subexpression elimination | en |
dc.subject | Modelling | en |
dc.subject | Reformulation | en |
dc.subject | Propositional satisfiability | en |
dc.subject | QA75 Electronic computers. Computer science | en |
dc.subject | QA76 Computer software | en |
dc.subject | Language and Linguistics | en |
dc.subject | Artificial Intelligence | en |
dc.subject | Linguistics and Language | en |
dc.subject | NDAS | en |
dc.subject | BDC | en |
dc.subject | R2C | en |
dc.subject | ~DC~ | en |
dc.subject.lcc | QA75 | en |
dc.subject.lcc | QA76 | en |
dc.title | Automatically improving constraint models in Savile Row | en |
dc.type | Journal article | en |
dc.contributor.sponsor | EPSRC | en |
dc.contributor.sponsor | EPSRC | en |
dc.contributor.sponsor | EPSRC | en |
dc.contributor.sponsor | The Royal Society | en |
dc.contributor.institution | University of St Andrews. School of Computer Science | en |
dc.contributor.institution | University of St Andrews. Centre for Interdisciplinary Research in Computational Algebra | en |
dc.identifier.doi | 10.1016/j.artint.2017.07.001 | |
dc.description.status | Peer reviewed | en |
dc.date.embargoedUntil | 2018-07-13 | |
dc.identifier.grantnumber | EP/H004092/1 | en |
dc.identifier.grantnumber | EP/K015745/1 | en |
dc.identifier.grantnumber | EP/M003728/1 | en |
dc.identifier.grantnumber | UF1204070 | en |
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