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Range and Roots: Two common patterns for specifying and propagating counting and occurrence constraints

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Title: Range and Roots: Two common patterns for specifying and propagating counting and occurrence constraints
Authors: Bessiere, Christian1 bessiere@lirmm.fr, Hebrard, Emmanuel2 e.hebrard@4c.ucc.ie, Hnich, Brahim3 brahim.hnich@ieu.edu.tr, Kiziltan, Zeynep4 zeynep@cs.unibo.it, Walsh, Toby5 tw@cse.unsw.edu.au
Source: Artificial Intelligence. Jul2009, Vol. 173 Issue 11, p1054-1078. 25p.
Subjects: Constraint programming, Constraint satisfaction, Mathematical decomposition, Algorithms, Pattern perception, Computer programming, Computer science literature
Abstract: Abstract: We propose Range and Roots which are two common patterns useful for specifying a wide range of counting and occurrence constraints. We design specialised propagation algorithms for these two patterns. Counting and occurrence constraints specified using these patterns thus directly inherit a propagation algorithm. To illustrate the capabilities of the Range and Roots constraints, we specify a number of global constraints taken from the literature. Preliminary experiments demonstrate that propagating counting and occurrence constraints using these two patterns leads to a small loss in performance when compared to specialised global constraints and is competitive with alternative decompositions using elementary constraints. [Copyright &y& Elsevier]
Copyright of Artificial Intelligence is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 40635478
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PubTypeId: academicJournal
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  Data: Range and Roots: Two common patterns for specifying and propagating counting and occurrence constraints
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  Data: <searchLink fieldCode="DE" term="%22Constraint+programming%22">Constraint programming</searchLink><br /><searchLink fieldCode="DE" term="%22Constraint+satisfaction%22">Constraint satisfaction</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+decomposition%22">Mathematical decomposition</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Pattern+perception%22">Pattern perception</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+programming%22">Computer programming</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+science+literature%22">Computer science literature</searchLink>
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  Data: Abstract: We propose Range and Roots which are two common patterns useful for specifying a wide range of counting and occurrence constraints. We design specialised propagation algorithms for these two patterns. Counting and occurrence constraints specified using these patterns thus directly inherit a propagation algorithm. To illustrate the capabilities of the Range and Roots constraints, we specify a number of global constraints taken from the literature. Preliminary experiments demonstrate that propagating counting and occurrence constraints using these two patterns leads to a small loss in performance when compared to specialised global constraints and is competitive with alternative decompositions using elementary constraints. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Artificial Intelligence is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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