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Machine learning for constraint solver design -- A case study for the alldifferent constraint [article]

Ian Gent and Lars Kotthoff and Ian Miguel and Peter Nightingale
2010 arXiv   pre-print
We investigate using machine learning to make these decisions automatically depending on the problem to solve. We use the alldifferent constraint as a case study.  ...  Constraint solvers are complex pieces of software which require many design decisions to be made by the implementer based on limited information.  ...  We thank Jesse Hoey for useful discussions about machine learning and the anonymous reviewers for their feedback. Peter Nightingale is supported by EPSRC grants EP/H004092/1 and EP/E030394/1.  ... 
arXiv:1008.4326v1 fatcat:3dkjodeuybarvhg45nn4y2r2hm

Automatically improving constraint models in Savile Row

Peter Nightingale, Özgür Akgün, Ian P. Gent, Christopher Jefferson, Ian Miguel, Patrick Spracklen
2017 Artificial Intelligence  
Using a CP solver, we obtained a geometric mean of 5.96 times speedup for instances taking over 10 seconds to solve.  ...  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.  ...  Acknowledgements We would like to thank the EPSRC for funding this work through grants EP/H004092/1, EP/K015745/1, EP/M003728/1, and EP/P015638/1.  ... 
doi:10.1016/j.artint.2017.07.001 fatcat:tu565j3nbrc2ragicqu5ozqczq

Combining CP and ILP in a Tree Decomposition of Bounded Height for the Sum Colouring Problem [chapter]

Maël Minot, Samba Ndojh Ndiaye, Christine Solnon
2017 Lecture Notes in Computer Science  
It consists in finding a proper colouring which minimizes the sum of the assigned colours rather than the number of those colours. This problem often arises in scheduling and resource allocation.  ...  The sum colouring problem An undirected graph G = (V, E) is defined by a set V of nodes and a set E ⊆ V × V of edges. Each edge of G is an undirected pair of nodes. We note  ...  Acknowledgements This work has been supported by the ANR project SoLStiCe (ANR-13-BS02-0002-01).  ... 
doi:10.1007/978-3-319-59776-8_29 fatcat:dailnbi6wvce5bz4zh2mdqbmqe

Benchmarking Symbolic Execution Using Constraint Problems – Initial Results [article]

Sahil Verma, Roland H.C. Yap
2020 arXiv   pre-print
Symbolic execution is a powerful technique for bug finding and program testing. It is successful in finding bugs in real-world code.  ...  The core reasoning techniques use constraint solving, path exploration, and search, which are also the same techniques used in solving combinatorial problems, e.g., finite-domain constraint satisfaction  ...  ACKNOWLEDGEMENT We acknowledge the support of R-252-000-592-112 and R-252-000-A39-112. We would like to thank Andrew Santosa who helped with a preliminary version of this work.  ... 
arXiv:2001.07914v1 fatcat:xv3spzw6anghjohlz2iipi6jmq

Short Portfolio Training for CSP Solving [article]

Mirko Stojadinović, Mladen Nikolić, Filip Marić
2015 arXiv   pre-print
Thorough evaluation has been performed and has shown that the approach yields good results. We evaluated several machine learning techniques for our portfolio.  ...  However, there is no single solver (nor approach) that performs well on all classes of problems and many portfolio approaches for selecting a suitable solver based on simple syntactic features of the input  ...  Acknowledgements This work was partially supported by the Serbian Ministry of Science grant 174021.  ... 
arXiv:1505.02070v1 fatcat:4l4f5el7tndsfn4iuhoaz2n56q

Estimating the Number of Solutions of Cardinality Constraints Through $$\texttt {range}$$ and $$\texttt {roots}$$ Decompositions [chapter]

Giovanni Lo Bianco, Xavier Lorca, Charlotte Truchet
2019 Lecture Notes in Computer Science  
This paper introduces a systematic approach for estimating the number of solutions of cardinality constraints.  ...  A main difficulty of solutions counting on a specific constraint lies in the fact that it is, in general, at least as hard as developing the constraint and its propagators, as it has been shown on alldifferent  ...  Such a question arises, for instance, in several works on probabilistic reasoning and machine learning [8, 9] , or when exploring the structure of the solution space [17] .  ... 
doi:10.1007/978-3-030-30048-7_19 fatcat:6ymmfeauoza5via26cp74etetq

Proteus: A Hierarchical Portfolio of Solvers and Transformations [chapter]

Barry Hurley, Lars Kotthoff, Yuri Malitsky, Barry O'Sullivan
2014 Lecture Notes in Computer Science  
There are also a number of different encodings for representing CSPs as SAT instances.  ...  Our experimental evaluation used an instance of Proteus that involved four CSP solvers, three SAT encodings, and six SAT solvers, evaluated on the most challenging problem instances from the CSP solver  ...  The Insight Centre for Data Analytics is supported by SFI Grant SFI/12/RC/2289.  ... 
doi:10.1007/978-3-319-07046-9_22 fatcat:5brcnwy2hrcv3o4mqizj225d5a

Proteus: A Hierarchical Portfolio of Solvers and Transformations [article]

Barry Hurley, Lars Kotthoff, Yuri Malitsky, Barry O'Sullivan
2014 arXiv   pre-print
There are also a number of different encodings for representing CSPs as SAT instances.  ...  Our experimental evaluation used an instance of Proteus that involved four CSP solvers, three SAT encodings, and six SAT solvers, evaluated on the most challenging problem instances from the CSP solver  ...  The Insight Centre for Data Analytics is supported by SFI Grant SFI/12/RC/2289.  ... 
arXiv:1306.5606v2 fatcat:5x4x3svdavemdjkjrxljqhsapy

Industrial Applications of Answer Set Programming

Andreas Falkner, Gerhard Friedrich, Konstantin Schekotihin, Richard Taupe, Erich C. Teppan
2018 Künstliche Intelligenz  
The knowledge representation and reasoning (KRR) framework of answer set programming (ASP) offers a rich representation language and high performance solvers.  ...  Therefore, ASP has become very attractive for the representation and solving of search-problems both for academia and industry. This article focuses on the latest industrial applications of ASP.  ...  distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were  ... 
doi:10.1007/s13218-018-0548-6 fatcat:sa674g4zjfeitkct5nnyl3ujea

Learning constraints in spreadsheets and tabular data

Samuel Kolb, Sergey Paramonov, Tias Guns, Luc De Raedt
2017 Machine Learning  
We propose a two-stage generate and test method where the first stage uses constraint solving techniques to efficiently reduce the number of candidates, based on the predicate signatures.  ...  We investigate the automatic learning of constraints (formulas and relations) in raw tabular data in an unsupervised way.  ...  Acknowledgements This work has been partially funded by the ERC AdG SYNTH (Synthesising inductive data models) and a PhD and Postdoctoral Fellowship of the Research Foundation-Flanders.  ... 
doi:10.1007/s10994-017-5640-x fatcat:zjvo37wiwrbxxk4pwenmnir2v4

Models for Global Constraint Applications

Helmut Simonis
2006 Constraints  
We look at three systems from different application domains and show the core models used to express their constraints.  ...  In this paper we give an overview of some industrial applications built using global constraints.  ...  an airport in Korea [63] . • The second case study (section 3) is the MOSES feed mill scheduling system [55, 4] , a complex, multi-resource production scheduling system with an interactive problem solver  ... 
doi:10.1007/s10601-006-9011-7 fatcat:mb5ojgblzzbsdf4cej55wps67i

Tracking Road Users using Constraint Programming [article]

Alexandre Pineault, Guillaume-Alexandre Bilodeau, Gilles Pesant
2020 arXiv   pre-print
We present a constraint programming (CP) approach for the data association phase found in the tracking-by-detection paradigm of the multiple object tracking (MOT) problem.  ...  Constraints are defined on these two features and on the general MOT problem.  ...  This is a common requirement for which CP provides an AllDifferent constraint. Such constraints have been specified for this purpose using the same variables as the previous equations.  ... 
arXiv:2003.04468v1 fatcat:wfuyiqbb5nbslaab2wt6sprvsa

XCSP3: An Integrated Format for Benchmarking Combinatorial Constrained Problems [article]

Frederic Boussemart and Christophe Lecoutre and Gilles Audemard and Cédric Piette
2021 arXiv   pre-print
As a result, XCSP3 encompasses practically all constraints that can be found in major constraint solvers developed by the CP community.  ...  A website, which is developed conjointly with the format, contains many models and series of instances. The user can make sophisticated queries for selecting instances from very precise criteria.  ...  Acknowledgments This work has been supported by both CNRS and OSEO (BPI France) within the ISI project 'Pajero'.  ... 
arXiv:1611.03398v3 fatcat:zxfjdsshgjc43btc734mdd3kcu

An Enhanced Features Extractor for a Portfolio of Constraint Solvers [article]

Roberto Amadini and Maurizio Gabbrielli and Jacopo Mauro
2014 arXiv   pre-print
The solver selection is usually done by means of (un)supervised learning techniques which exploit features extracted from the problem specification.  ...  Recent research has shown that a single arbitrarily efficient solver can be significantly outperformed by a portfolio of possibly slower on-average solvers.  ...  For example, the alldifferent global constraint is decomposed by default into a conjunction of inequalities.  ... 
arXiv:1308.0227v7 fatcat:4kjv7ml6ifbmrkmtlmjwkf3gbq

Machine Learning of Bayesian Networks Using Constraint Programming [chapter]

Peter van Beek, Hella-Franziska Hoffmann
2015 Lecture Notes in Computer Science  
In this paper, we present a constraint-based depth-first BnB approach for solving the Bayesian network learning problem.  ...  for a minimum cost solution to the model.  ...  We are not aware of any reports of results for exact solvers for instances beyond the medium class (Barlett and Acknowledgements This research was partially funded through an NSERC Discovery Grant.  ... 
doi:10.1007/978-3-319-23219-5_31 fatcat:r42i55ctzvaezhl5tncqgdpzpy
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