References

 
Structure Learning and Gene Regulatory Networks
2
Lise Pomiès, Céline Brouard, Harold Duruflé, Élise Maigné, Clément Carré, Louise Gody, Fulya Trösser, George Katsirelos, Brigitte Mangin, Nicolas B Langlade, and Simon de Givry
Gene regulatory network inference methodology for genomic and transcriptomic data acquired in genetically related heterozygote individuals
Bioinformatics, 38(17):4127–4134, 07 2022
3
Fulya Trösser, Simon de Givry, and George Katsirelos
Structured Set Variable Domains in Bayesian Network Structure Learning
In Proc. of CP-22, volume 235, pages 37:1–37:9, Haifa, Israel, 2022
4
Fulya Trösser, Simon de Givry, and George Katsirelos
Improved acyclicity reasoning for bayesian network structure learning with constraint programming
In Proc. of IJCAI-21, Montreal, Canada, 2021
5
David Allouche, Christine Cierco-Ayrolles, Simon de Givry, G Guillermin, Brigitte Mangin, Thomas Schiex, Jimmy Vandel, and Matthieu Vignes
Gene Network Inference, chapter A Panel of Learning Methods for the Reconstruction of Gene Regulatory Networks in a Systems Genetics Contex
Springer, 2014
6
J Vandel, B Mangin, and S de Givry
New Local Move Operators for Bayesian Network Structure Learning
In Proc. of PGM-12, Granada, Spain, 2012
7
Matthieu Vignes, Jimmy Vandel, David Allouche, Nidal Ramadan-Alban, Christine Cierco-Ayrolles, Thomas Schiex, Brigitte Mangin, and Simon de Givry
Gene regulatory network reconstruction using bayesian networks, the dantzig selector, the lasso and their meta-analysis
PLoS ONE, 6(12), 2011
 
Agronomy and Operations Research
9
Sara Maqrot, Simon de Givry, Gauthier Quesnel, and Marc Tchamitchian
A Mixed Integer Programming Reformulation of the Mixed Fruit-Vegetable Crop Allocation Problem
In 30th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems (IEA/AIE), page 12 pages, Arras, France, June 2017
10
Mahuna Akplogan, Simon de Givry, Jean-Philippe Métivier, Gauthier Quesnel, Alexandre Joannon, and Frédérick Garcia
Solving the crop allocation problem using hard and soft constraints
RAIRO - Operations Research, 47:151–172, 2013
 
Bioinformatics
12
Manon Ruffini, Jelena Vucinic, Simon de Givry, George Katsirelos, Sophie Barbe, and Thomas Schiex
Guaranteed diversity and optimality in cost function network based computational protein design methods
Algorithms, 14(6):168, 2021
13
François Beuvin, Simon de Givry, Thomas Schiex, Sébastien Verel, and David Simoncini
Iterated local search with partition crossover for computational protein design
Proteins: Structure, Function, and Bioinformatics, 2021
14
David Allouche, Sophie Barbe, Simon de Givry, George Katsirelos, Yahia Lebbah, Samir Loudni, Abdelkader Ouali, Thomas Schiex, David Simoncini, and Matthias Zytnicki
Operations Research and Simulation in Healthcare, chapter Cost Function Networks to Solve Large Computational Protein Design Problems
Springer, 2021
15
Clément Viricel, Simon de Givry, Thomas Schiex, and Sophie Barbe
Cost function network-based design of protein-protein interactions: predicting changes in binding affinity
Bioinformatics, 34(15):2581–2589, 2018
16
D. Simoncini, D. Allouche, S. de Givry, C. Delmas, S. Barbe, and T. Schiex
Guaranteed discrete energy optimization on large protein design problems
Journal of Chemical Theory and Computation, 11(12):5980–5989, 2015
17
Seydou Traoré, David Allouche, Isabelle André, Simon de Givry, George Katsirelos, Thomas Schiex, and Sophie Barbe
A new framework for computational protein design through cost function network optimization
Bioinformatics, 29(17):2129–2136, 2013
http://bioinformatics.oxfordjournals.org/content/29/17/2129.abstract?keytype=ref&ijkey=6s5WwvLNn88x2ZB
18
B. Servin, S. de Givry, and T. Faraut
Statistical confidence measures for genome maps: application to the validation of genome assemblies
Bioinformatics, 26(24):3035–3042, 2010
19
M. Sanchez, S. de Givry, and T. Schiex
Mendelian error detection in complex pedigrees using weighted constraint satisfaction techniques
Constraints, 13(1):130–154, 2008
Special issue on Bioinformatics and Constraints. The original publication is available at http://www.springerlink.com
20
Patricia Thébault, Simon de Givry, Thomas Schiex, and Christine Gaspin
Searching RNA motifs and their intermolecular contacts with constraint networks
Bioinformatics, 22(17):2074–2080, 2006
21
T. Faraut, S. de Givry, P. Chabrier, T. Derrien, F. Galibert, C. Hitte, and T. Schiex
A comparative genome approach to marker ordering
Bioinformatics, 23(2):50–56, 2007
22
Simon de Givry, Martin Bouchez, Patrick Chabrier, Denis Milan, and Thomas Schiex
CARTHAGENE: multipopulation integrated genetic and radiated hybrid mapping
Bioinformatics, 21(8):1703–1704, 2005
 
Valued Constraint Satisfaction Problems
24
Samuel Buchet, David Allouche, Simon de Givry, and Thomas Schiex
Bi-objective discrete graphical model optimization
In Proc. of CP-AI-OR'2024, Uppsala, Sweden, 2024
25
Pierre Montalbano, David Allouche, Simon de Givry, George Katsirelos, and Tomáš Werner
Virtual pairwise consistency in cost function networks
In Proc. of CP-AI-OR'2023, Nice, France, 2023
26
Tomáš Dlask, Tomáš Werner, and Simon de Givry
Super-Reparametrizations of Weighted CSPs: Properties and Optimization Perspective
Constraints, 28:277–319, 2023
27
Abdelkader Beldjilali, Pierre Montalbano, David Allouche, George Katsirelos, and Simon de Givry
Parallel Hybrid Best-First Search
In Proc. of CP-22, volume 235, pages 7:1–7:10, Haifa, Israel, 2022
28
Pierre Montalbano, Simon de Givry, and George Katsirelos
Multiple-choice knapsack constraint in graphical models
In Proc. of CP-AI-OR'2022, Los Angeles, CA, 2022
29
Tomáš Dlask, Tomáš Werner, and Simon de Givry
Bounds on weighted csps using constraint propagation and super-reparametrizations
In Proc. of CP-21, Montpellier, France, 2021
30
Céline Brouard, Simon de Givry, and Thomas Schiex
Pushing data in cp models using graphical model learning and solving
In Proc. of CP-20, pages 881–827, Louvain-la-neuve, Belgium, 2020
31
Fulya Trösser, Simon de Givry, and George Katsirelos
Relaxation-aware heuristics for exact optimization in graphical models
In Proc. of CP-AI-OR'2020, pages 475–491, Vienna, Austria, 2020
32
Martin C. Cooper, Simon de Givry, and Thomas Schiex
Valued Constraint Satisfaction Problems, pages 185–207
Springer International Publishing, 2020
33
Martin C. Cooper, Simon de Givry, and Thomas Schiex
Graphical models: Queries, complexity, algorithms (tutorial)
In 37th International Symposium on Theoretical Aspects of Computer Science (STACS-20), volume 154 of LIPIcs, pages 4:1–4:22, Montpellier, France, 2020
34
Abdelkader Ouali, David Allouche, Simon de Givry, Samir Loudni, Yahia Lebbah, Lakhdar Loukil, and Patrice Boizumault
Variable neighborhood search for graphical model energy minimization
Artificial Intelligence, 278(103194):22p., 2020
35
Nathalie Peyrard, Marie-Josée Cros, Simon de Givry, Alain Franc, Stéphane Robin, Régis Sabbadin, Thomas Schiex, and Matthieu Vignes
Exact or approximate inference in graphical models: why the choice is dictated by the treewidth, and how variable elimination can be exploited
Australian & New Zealand Journal of Statistics, 61(2):89–133, 2019
36
M. Ruffini, J. Vucinic, S. de Givry, G. Katsirelos, S. Barbe, and T. Schiex
Guaranteed diversity & quality for the weighted csp
In Proc. of ICTAI-19, pages 18–25, Portland, OR, USA, 2019
37
S de Givry and G Katsirelos
Clique Cuts in Weighted Constraint Satisfaction
In Proc. of CP-17, pages 97–113, Melbourne, Australia, 2017
38
Abdelkader Ouali, David Allouche, Simon de Givry, Samir Loudni, Yahia Lebbah, Francisco Eckhardt, and Lakhdar Loukil
Iterative Decomposition Guided Variable Neighborhood Search for Graphical Model Energy Minimization
In Proc. of UAI-17, pages 550–559, Sydney, Australia, 2017
39
Hiep Nguyen, Christian Bessiere, Simon de Givry, and Thomas Schiex
Triangle-based Consistencies for Cost Function Networks
Constraints, 22(2):230–264, 2017
40
David Allouche, Christian Bessière, Patrice Boizumault, Simon de Givry, Patricia Gutierrez, Jimmy H.M. Lee, Ka Lun Leung, Samir Loudni, Jean-Philippe Métivier, Thomas Schiex, and Yi Wu
Tractability-preserving transformations of global cost functions
Artificial Intelligence, 238:166–189, 2016
41
B Hurley, B O'Sullivan, D Allouche, G Katsirelos, T Schiex, M Zytnicki, and S de Givry
Multi-Language Evaluation of Exact Solvers in Graphical Model Discrete Optimization
Constraints, 21(3):413–434, 2016
Presentation at CPAIOR'16, Banff, Canada, https://miat.inrae.fr/degivry/cpaior16sdg.pdf
42
D Allouche, S de Givry, G Katsirelos, T Schiex, and M Zytnicki
Anytime Hybrid Best-First Search with Tree Decomposition for Weighted CSP
In Proc. of CP-15, pages 12–28, Cork, Ireland, 2015
43
David Allouche, Jessica Davies, Simon de Givry, George Katsirelos, Thomas Schiex, Seydou Traoré, Isabelle André, Sophie Barbe, Steve Prestwich, and Barry O'Sullivan
Computational protein design as an optimization problem
Artificial Intelligence, 212:59–79, 2014
44
S de Givry, S Prestwich, and B O'Sullivan
Dead-End Elimination for Weighted CSP
In Proc. of CP-13, pages 263–272, Uppsala, Sweden, 2013
45
D Allouche, S Traoré, I André, S de Givry, G Katsirelos, S Barbe, and T Schiex
Computational protein design as a cost function network optimization problem
In Proc. of CP-12, Quebec City, Canada, 2012
46
D Allouche, C Bessiere, P Boizumault, S de Givry, P Gutierrez, S Loudni, JP Métivier, and T Schiex
Decomposing global cost functions
In Proc. of AAAI-12, Toronto, Canada, 2012
https://miat.inrae.fr/degivry/Ficolofo2012poster.pdf (poster)
47
A Favier, S de Givry, A Legarra, and T Schiex
Pairwise decomposition for combinatorial optimization in graphical models
In Proc. of IJCAI-11, Barcelona, Spain, 2011
Video demonstration at https://miat.inrae.fr/degivry/Favier11.mov
48
A. Favier, S. de Givry, and P. Jégou
Solution counting for CSP and SAT with large tree-width
Control Systems and Computers, (2):4–13, 2011
49
D. Allouche, S. de Givry, and T. Schiex
Towards parallel non serial dynamic programming for solving hard weighted csp
In Proc. of CP-10, St Andrews, Scotland, 2010
50
M. Cooper, S. de Givry, M. Sanchez, T. Schiex, M. Zytnicki, and T. Werner
Soft arc consistency revisited
Artificial Intelligence, (7–8):449–478, 2010
51
M. Zytnicki, C. Gaspin, S. de Givry, and T. Schiex
Bounds Arc Consistency for Weighted CSPs
Journal of Artificial Intelligence Research, 35:593–621, 2009
52
R. Marinescu, R. Dechter, S. de Givry, and T. Schiex
Combinatorial optimization for graphical models
IJCAI-09 tutorial, July 2009
https://miat.inrae.fr/degivry/tutorial_optimization_ijcai09.ppt
53
M Sanchez, D Allouche, S de Givry, and T Schiex
Russian doll search with tree decomposition
In Proc. of IJCAI-09, Pasadena (CA), USA, 2009
https://miat.inrae.fr/degivry/rdsbtd_ijcai09_sdg.ppt
54
M. Cooper, S. de Givry, M. Sanchez, T. Schiex, and M. Zytnicki
Virtual arc consistency for weighted csp
In Proc. of AAAI-08, Chicago, IL, 2008
55
J. Larrosa, F. Heras, and S. de Givry
A logical approach to efficient max-sat solving
Artificial Intelligence, 172(2–3):204–233, 2008
56
M. Cooper, S. de Givry, and T. Schiex
Optimal soft arc consistency
In Proc. of IJCAI-07, pages 68–73, Hyderabad, India, 2007
57
Simon de Givry, Thomas Schiex, and Gérard Verfaillie
Exploiting tree decomposition and soft local consistency in weighted csp
In Proc. of AAAI-06, Boston, MA, 2006
https://miat.inrae.fr/degivry/VerfaillieAAAI06pres.pdf (slides)
58
S. de Givry, M. Zytnicki, F. Heras, and J. Larrosa
Existential arc consistency: Getting closer to full arc consistency in weighted csps
In Proc. of IJCAI-05, pages 84–89, Edinburgh, Scotland, 2005
59
S. de Givry, J. Larrosa, P. Meseguer, and T. Schiex
Solving max-sat as weighted csp
In Proc. of CP-03, pages 363–376, Kinsale, County Cork, Ireland, 2003
60
Bertrand Cabon, Simon de Givry, and Gérard Verfaillie
Anytime Lower Bounds for Constraint Optimization Problems
In Proc. of CP-98, pages 117–131, Pisa, Italy, October 26-30 1998
61
Simon de Givry, Gérard Verfaillie, and Thomas Schiex
Bounding the Optimum of Constraint Optimization Problems
In Proc. of CP-97, pages 405–419, Schloss Hagenberg, Austria, October 29 - November 1 1997
 
Constraint Programming
63
Thomas Schiex and Simon de Givry, editors
Principles and Practice of Constraint Programming - 25th International Conference, CP 2019, Stamford, CT, USA, September 30 - October 4, 2019, Proceedings, volume 11802 of Lecture Notes in Computer Science. Springer, 2019
64
S. de Givry and L. Jeannin
A unified framework for partial and hybrid search methods in constraint programming
Computer & Operations Research, 33(10):2805–2833, 2006
65
S. de Givry, L. Jeannin, F. Josset, J. Mattioli, N. Museux, and P. Savéant
The thales constraint programming framework for hard and soft real-time applications
The PLANET Newsletter, Issue 5 ISSN 1610-0212, pages 5-7, December 2002
http://planet.dfki.de/service/Resources/Rome/degivry.pdf (slides)
66
S. de Givry, Y. Hamadi, J. Mattioli, P. Gérard, M. Lema&̂#305;tre, G. Verfaillie, A. Aggoun, I. Gouachi, T. Benoist, E. Bourreau, F. Laburthe, P. David, S. Loudni, and S. Bourgault
Towards an on-line optimisation framework
In CP-2001 Workshop on On-Line combinatorial problem solving and ConstraintProgramming (OLCP'01), pages 45–61, Paphos, Cyprus, December 1 2001
67
Jean Jourdan, Simon de Givry, and Pierre Savéant
Designing limited search algorithms for time constrained combinatorial optimization problems
Technical report, Thales Research & Development, 1999