SST/EPL Ecole polytechnique de Louvain (EPL)
SST/ICTM Institute of Information and Communication Technologies, Electronics and Applied Mathematics (ICTEAM)
SST/ICTM/INGI Pôle en ingénierie informatique (INGI)
Réseaux sociaux
2026
Document de travail
Kiossou, H., Schaus, P., & Nijssen, S. (2026). Anytime Optimal Decision Tree Learning with Continuous Features.
2025
Document de travail
Delecluse, A., Schaus, P., & Van Hentenryck, P. (2025). Sequence Variables: A Constraint Programming Computational Domain for Routing and Sequencing.
Schaus, P., Thomas, C., & Kameugne, R. (2025). Implementing Cumulative Functions with Generalized Cumulative Constraints.
Thomas, C., & Schaus, P. (2025). Solving the Aircraft Disassembly Scheduling Problem.
Schaus, P., Delecluse, A., & Derval, G. (2025). ICLF: An Immersive Code Learning Framework based on Git for Teaching and Evaluating Student Programming Projects.
Kiossou, H., Nijssen, S., & Schaus, P. (2025). A Generic Complete Anytime Beam Search for Optimal Decision Tree.
Papier de conférence
Crespin, A., Kostis, I., Verhaeghe, H., & Schaus, P. (2025). CP-Model-Zoo: A Natural Language Query System for Constraint Programming Models. Workshop LLM-solve of CP2025, Glasgow, UK.
Burlats, A., Pelsser, C., & Schaus, P. (2025). Sélection quasi-optimale de routes pour la surveillance de réseaux à l’aide de la génération de colonnes. Journées Francophones de Programmation par Contraintes 2025, Dijon, France.
Legrand, E., Coppé, V., Catanzaro, D., & Schaus, P. (2025). A Dynamic Programming Approach for the Job Sequencing and Tool Switching Problem. Lecture Notes in Computer Science : Integration of Constraint Programming, Artificial Intelligence, and Operations Research, p. 70-85. https://doi.org/10.1007/978-3-031-95976-9_5
2024
Article de journal
Coppé, V., Gillard, X., & Schaus, P. (2024). Decision Diagram-Based Branch-and-Bound with Caching for Dominance and Suboptimality Detection. Informs Journal on Computing, 36(6), 1359-1756. https://doi.org/10.1287/ijoc.2022.0340 (Original work published 2024)
Coppé, V., Gillard, X., & Schaus, P. (2024). Decision Diagram-Based Branch-and-Bound with Caching for Dominance and Suboptimality Detection. INFORMS Journal on Computing. Submitted. https://doi.org/10.1287/ijoc.2022.0340 (Original work published 2024)
Stefanija Veljanoska, Nijssen, S., Schaus, P., John Aoga, & Juhee Bae. (2024). Impact of Weather Factors on Migration Intention using Machine Learning Algorithms. Operations Research Forum, Volume 5(number 8). https://doi.org/10.1007/s43069-023-00271-y (Original work published 2024)
Papier de conférence
Burlats, A., Schaus, P., & Pelsser, C. (2024). An Exploration of Exact Methods for Effective Network Failure Detection and Diagnosis. An Exploration of Exact Methods for Effective Network Failure Detection and Diagnosis, p. 153-169. https://doi.org/10.1007/978-3-031-60597-0_11
Dubray, A., Schaus, P., & Nijssen, S. (2024). Anytime Weighted Model Counting with Approximation Guarantees For Probabilistic Inference. International Conference on Principles and Practice of Constraint Programming, Girona, Spain.
Delecluse, A., & Schaus, P. (2024). Black-Box Value Heuristics for Solving Optimization Problems with Constraint Programming - Extended abstract.
Burlats, A., Pelsser, C., & Schaus, P. (2024). Une exploration de méthodes exactes pour une détection et un diagnostic efficaces des défaillances des réseaux. Journées Francophones de Programmation par Contraintes 2024, Lean, France.
Véjar, B., Aglin, G., Mahmutoğulları, A. İ., Nijssen, S., Schaus, P., & Guns, T. (2024). An Efficient Structured Perceptron for NP-Hard Combinatorial Optimization Problems. LNCS, 14743 (2024). https://doi.org/10.1007/978-3-031-60599-4_17 (Original work published 2024)
Kiossou, H., Schaus, P., Nijssen, S., & Aglin, F. (2024). Efficient Lookahead Decision Trees. Lecture Notes in Computer Science : Advances in Intelligent Data Analysis XXII, p. 133-144. https://doi.org/10.1007/978-3-031-58553-1_11
Burlats, A., Pelsser, C., & Schaus, P. (2024). An Exploration of Exact Methods for Effective Network Failure Detection and Diagnosis. 38th Annual Conference of the Belgian Operational Research Society, Antwerp, Belgium.
Coppé, V., Gillard, X., & Schaus, P. (2024). Modeling and Exploiting Dominance Rules for Discrete Optimization with Decision Diagrams. Integration of Constraint Programming, Artificial Intelligence, and Operations Research : Lecture Notes in Computer Science, p. 226-242. https://doi.org/10.1007/978-3-031-60597-0_15
Delecluse, A., & Schaus, P. (2024). Black-Box Value Heuristics for Solving Optimization Problems with Constraint Programming (Short Paper).
Thomas, C., & Schaus, P. (2024). A Constraint Programming Approach for Aircraft Disassembly Scheduling. Lecture Notes in Computer Science, 14743. https://doi.org/10.1007/978-3-031-60599-4_13 (Original work published 2024)
Schaus, P., & Delecluse, A. (2024). Black-Box Value Heuristics for Solving Optimization Problems with Constraint Programming.
2023
Papier de conférence
Golenvaux, Gillard, X., Nijssen, S., & Schaus, P. (2023). Partitioning a Map into Homogeneous Contiguous Regions: A Branch-And-Bound Approach Using Decision Diagrams. Leibniz International Proceedings in Informatics (LIPIcs). Published. 29th International Conference on Principles and Practice of Constraint Programming (CP 2023), Toronto, Canada. https://doi.org/10.4230/LIPIcs.CP.2023.45 (Original work published 2023)
Coppé, V., Gillard, X., & Schaus, P. (2023). Accélération de l’algorithme de séparation et évaluation pour les diagrammes de décision grâce à la mémoïsation. Journées Francophones de Programmation par Contraintes, Strasbourg, France.
Burlats, A., Schaus, P., & Pelsser, C. (2023). Placement optimal de moniteurs dans un réseau pour la tomographie booléenne. Journées Francophones de Programmation par Contraintes, Strasbourg, France.
Delecluse, A., Schaus, P., & Pascal Van Hentenryck. (2023). SEQUOIA: SEQuence-variable-based Optimization In Action for the Traveling Salesman Problem with Time Windows. Doctoral Program of CP23, Toronto.
Coppé, V., Gillard, X., & Schaus, P. (2023). Boosting Decision Diagram-Based Branch-and-Bound by Pre-Solving with Aggregate Dynamic Programming. The 29th International Conference on Principles and Practice of Constraint Programming, Toronto, Canada.
Delecluse, A., Derval, G., Michel, L., Schaus, P., & Van Hentenryck, P. (2023). A review of the Constraint Programming MOOC on EdX. Workshop on Teaching Constraint Programming, WTCP 2023, 1(3), 14. (Original work published 2023)
Dubray, A., Schaus, P., & Nijssen, S. (2023). Probabilistic Inference by Projected Weighted Model Counting on Horn Clauses. Proceedings CP 2023. Published. International Conference on Principles and Practice of Constraint Programming, Toronto, Canada. (Original work published 2023)
2022
Papier de conférence
Coppé, V., Gillard, X., & Schaus, P. (2022). Optimiser l’agencement d’une fabrique grâce aux diagrammes de décision. Journées Francophones de Programmation par Contraintes, Saint-Étienne, France.
Coppé, V., Gillard, X., & Schaus, P. (2022). Solving the Constrained Single-Row Facility Layout Problem with Decision Diagrams. 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Published. 28th International Conference on Principles and Practice of Constraint Programming (CP 2022), Haifa, Israel. https://doi.org/10.4230/LIPIcs.CP.2022.14
Coppé, V., & Schaus, P. (2022). A Conflict Avoidance Table for Continuous Conflict-Based Search. Proceedings of the International Symposium on Combinatorial Search, 15(1), 264-266. (Original work published 2022)
Gillard, X., & Schaus, P. (2022). Large Neighborhood Search with Decision Diagrams. International Joint Conference on Artificial Intelligence, Vienna, Austria.
Kiossou, H., Schaus, P., Nijssen, S., & Houndji, R. (2022). Time constrained DL8.5 using Limited Discrepancy Search. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. Accepted/in-press. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Grenoble, France. (Original work published 2022)
Dubray, A., Derval, G., Nijssen, S., & Schaus, P. (2022). Optimal Decoding of Hidden Markov Models With Consistency Constraints. Proceedings of the 25th International Conference on Discovery Science. Published. International Conference on Discovery Science, Montpellier, France. (Original work published 2022)
Aglin, G., Nijssen, S., & Schaus, P. (2022). Learning Optimal Decision Trees Under Memory Constraints. European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), Grenoble, France.
Delecluse, A., Schaus, P., & Van Hentenryck, P. (2022). Sequence Variables for Routing Problems.
Document de travail
Dubray, A., Derval, G., Nijssen, S., & Schaus, P. (2022). On The Complexity of the Shortest Path Problem in a Layered Directed Acyclic Graph with Consistency Constraints.
Augustin Delecluse, Schaus, P., & Van Hentenryck, P. (2022). Extended Abstract: Sequence Variables for Routing Problems.
Rapport
Cédric de Bontridder, Céline Everaert, Derval, G., & Schaus, P. (2022). Impact du réseau de transport en commun sur les critères du décret Inscription.
Article de journal
Docquier, F., Golenvaux, N., Nijssen, S., Schaus, P., & Stips, F. (2022). Cross-border mobility responses to COVID-19 in Europe: new evidence from facebook data. Globalization and Health, 18(1), 0-17. https://doi.org/10.1186/s12992-022-00832-6 (Original work published 2022)
2021
Article de journal
Laurent Michel, Schaus, P., & Pascal Van Hentenryck. (2021). MiniCP: a lightweight solver for constraint programming. Mathematical Programming Computation, 13(1), 133-184. https://doi.org/10.1007/s12532-020-00190-7 (Original work published 2021)
Derval, G., & Schaus, P. (2021). Maximal-Sum submatrix search using a hybrid contraint programming/linear programming approach. European Journal of Operational Research. Published. https://doi.org/10.1016/j.ejor.2021.06.008 (Original work published 2021)
Mattenet, L., Davidson, I., Nijssen, S., & Schaus, P. (2021). Generic Constraint-based Block Modeling using Constraint Programming. Journal of Artificial Intelligence Research, 70(1), 597-630. https://doi.org/10.1613/jair.1.12280 (Original work published 2021)
Dellicour, S., Linard, C., Van Goethem, N., Da Re, D., Artois, J., Bihin, J., Schaus, P., Massonnet, F., Van Oyen, H., Vanwambeke, S., Speybroeck, N., & Gilbert, M. (2021). Investigating the drivers of the spatio-temporal heterogeneity in COVID-19 hospital incidence—Belgium as a study case. International Journal of Health Geographics, 20(1), 1. https://doi.org/10.1186/s12942-021-00281-1 (Original work published 2021)
Papier de conférence
Dubray, A., Nijssen, S., Thomas, I., & Schaus, P. (2021). A Seriation Based Framework to Visualize Multiple Aspects of Road Transport from GPS Trajectories. IEEE Intelligent Transportation Systems Conference. Proceedings. Published. International Intelligent Transportation System Conference, Indianapolis, IN, USA. (Original work published 2021)
Gillard, X. (2021). Improving the filtering of Branch-And-BoundMDD solver (extended).
Verhaeghe, H., Nijssen, S., Pesant, G., Quimper, C.-G., & Schaus, P. (2021). Apprentissage d’arbres de décision optimaux grâce à la programmation par contraintes. Seizième journées Francophones de Programmation par Contraintes (JFPC21), Nice, France (Online).
Verhaeghe, H., Kameugne, R., Lecoutre, C., & Schaus, P. (2021). Improved Filtering of Scheduling Problems using Redundant Table Constraints. Workshop ModRef2021 of CP2021, Montpellier, France (Online).
Aglin, G., Nijssen, S., & Schaus, P. (2021). Assessing Optimal Forests of Decision Trees. 2021 IEEE 33rd International Conference on Tools with Artificial Intelligence (ICTAI). Published. International Conference on Tools with Artificial Intelligence (ICTAI). https://doi.org/10.1109/ICTAI52525.2021.00013
Chapitre de livre
Gillard, X. (2021). Improving the Filtering of Branch-and-Bound MDD Solver. In Peter J Stuckey (ed.), Integration of Constraint Programming, Artificial Intelligence, and Operations Research : Lecture Notes in Computer Science (p. p. 231-247). Springer. https://doi.org/10.1007/978-3-030-78230-6_15
2020
Papier de conférence
Gillard, X. (2020). Ddo, a Generic and Efficient Framework for MDD-Based Optimization.
Kiossou, H., Schenk, Y., Docquier, F., Houdji, V. R., Nijssen, S., & Schaus, P. (2020). Using an interpretable Machine Learning approach to study the drivers of International Migration. AI4SG. Published. AI For Social Good 2020. (Original work published 2020)
Derval, G., François-Lavet, V., & Schaus, P. (2020). Nowcasting COVID-19 hospitalizations using Google Trends and LSTM. AI4SG 2020. Accepted/in-press. AI4SG. (Original work published 2020)
Aglin, G., Nijssen, S., & Schaus, P. (2020). PyDL8.5: a Library for Learning Optimal Decision Trees. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, p. 5222-5224.
Aglin, G., Nijssen, S., & Schaus, P. (2020). Learning Optimal Decision Trees Using Caching Branch-and-Bound Search. Thirty-Fourth AAAI Conference on Artificial Intelligence, New york.
Verhaeghe, H., Nijssen, S., Pesant, G., Quimper, C.-G., & Schaus, P. (2020). Learning Optimal Decision Trees using Constraint Programming (Extended Abstract). Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI2020, 2020(1), 4765-4769. (Original work published 2020)
Dubray, A., Derval, G., Nijssen, S., & Schaus, P. (2020). Mining Constrained Regions of Interest: An Optimization Approach. Proceedings Discovery Science 2020. Published. Discovery Science 2020. (Original work published 2020)
Schaus, P., Thomas, C., Kameugne, R., & et al. (2020). Insertion Sequence Variables for Hybrid Routing and Scheduling Problems. 17th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, Online.
Article de journal
Verhaeghe, H., Nijssen, S., Pesant, G., Quimper, C.-G., & Schaus, P. (2020). Learning Optimal Decision Trees using Constraint Programming. Constraints Journal, 25(3-4), 226-250. https://doi.org/10.1007/s10601-020-09312-3 (Original work published 2020)
Mattenet, A., Davidson, I., Nijssen, S., & Schaus, P. (2020). Generic Constraint-based Block Modeling using Constraint Programming. Thirty-Fourth AAAI Conference on Artificial Intelligence Thirty-Second Conference on Innovative Applications of Artificial Intel, 34(9), 13685-13688. https://doi.org/10.1609/aaai.v34i09.7121 (Original work published 2020)
Van Cauwelaert, S., Dejemeppe, C., & Schaus, P. (2020). An Efficient Filtering Algorithm for the Unary Resource Constraint with Transition Times and Optional Activities. Journal of Scheduling, 23(4), 431-449. https://doi.org/10.1007/s10951-019-00632-8 (Original work published 2020)
2019
Article de journal
Mattenet, A., Davidson, I., Nijssen, S., & Schaus, P. (2019). Generic Constraint-based Block Modeling using Constraint Programming. C E U R Workshop Proceedings, 2491(1), 1. (Original work published 2019)
Branders, V., Schaus, P., & Dupont, P. (2019). Identifying gene-specific subgroups: an alternative to biclustering. BMC Bioinformatics, 20(625), 13. https://doi.org/10.1186/s12859-019-3289-0 (Original work published 2019)
Houndji, V. R., Schaus, P., & Wolsey, L. (2019). The item dependent stocking cost constraint. Constraints : an international journal, 24(2), 183-209. https://doi.org/10.1007/s10601-018-9300-y (Original work published 2019)
Alex Mattenet, Ian Davidson, Nijssen, S., & Schaus, P. (2019). Generic Constraint-based Block Modeling using Constraint Programming. Constraints : an international journal, 25(1), ?? (Original work published 2019)
Mattenet, A., Ian Davidson, Nijssen, S., & Schaus, P. (2019). Generic Constraint-based Block Modeling using Constraint Programming. Lecture Notes in Computer Science, 11802(1), 656-673. https://doi.org/10.1007/978-3-030-30048-7_38 (Original work published 2019)
Papier de conférence
Aoga, J., Nijssen, S., & Schaus, P. (2019). Modeling Pattern Set Mining using Boolean Circuits. the 25th International Conference on Principles and Practice of Constraint Programming, Stamford, CT, U.S.
Derval, G., Docquier, F., & Schaus, P. (2019). An aggregate learning approach for interpretable semi-supervised population prediction and disaggregation using ancillary data. Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2019., Lecture Notes in Computer Science(11908). (Original work published 2019)
Branders, V., Derval, G., Schaus, P., & Dupont, P. (2019). Mining a Maximum Weighted Set of Disjoint Submatrices. Discovery Science : Lecture Notes in Computer Science, p. 18-28. https://doi.org/10.1007/978-3-030-33778-0_2
Jadin, M., Aubry, F., Schaus, P., & Bonaventure, O. (2019). CG4SR: Near Optimal Traffic Engineering for Segment Routing with Column Generation. IEEE Infocom. Proceedings. Published. IEEE INFOCOM 2019, Paris. (Original work published 2019)
Gillard, X., Schaus, P., Deville, Y., & et al. (2019). SolverCheck: Declarative Testing of Constraints. Principles and Practice of Constraint Programming. Published. The 25th International Conference on Principles and Practice of Constraint Programming, Stamford, CT, USA. https://doi.org/10.1007/978-3-030-30048-7_33
Thomas, C., Cappart, Q., Schaus, P., & Rousseau, L.-M. (2019). Une approche de Programmation par Contraintes pour résoudre le Problème de Transport de Patients. JFPC 2019 - Actes des 15es Journées Francophones de Programmation par Contraintes, Albi, France, du 12-14 juin 2019, 31-32. (Original work published 2019)
Verhaeghe, H., Lecoutre, C., & Schaus, P. (2019). Compact-Diagram Propagateur efficace pour la contrainte (s)MDD. Quinzième journées Francophones de Programmation par Contraintes (JFPC19), Albi, France.
Verhaeghe, H., Nijssen, S., Pesant, G., Quimper, C.-G., & Schaus, P. (2019). Learning Optimal Decision Trees using Constraint Programming (abstract). Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch C, CEUR Workshop Proceedings(2491), 1. (Original work published 2019)
Verhaeghe, H., Lecoutre, C., & Schaus, P. (2019). Extension de Compact-Diagram aux smart MVD. Quinzième journées Francophones de Programmation par Contraintes (JFPC19), Albi, France.
Verhaeghe, H., Lecoutre, C., & Schaus, P. (2019). Extending Compact-Diagram to Basic Smart Multi-Valued Variable Diagrams. Integration of AI and OR Techniques in Constraint Programming 16th International Conference, CPAIOR 2019, Thessaloniki, Greece, 1(1), 581-598. (Original work published 2019)
Verhaeghe, H., Nijssen, S., Pesant, G., Quimper, C.-G., & Schaus, P. (2019). Learning Optimal Decision Trees using Constraint Programming. The 25th International Conference on Principles and Practice of Constraint Programming (CP2019), Stamford, USA.
Mattenet, A., Ian Davidson, Nijssen, S., & Schaus, P. (2019). Generic Constraint-based Block Modeling using Constraint Programming. 31st Benelux Conference on Artificial Intelligence (BNAIC 2019), Brussels.
Chapitre de livre
Derval, G., Branders, V., Dupont, P., & Schaus, P. (2019). The Maximum Weighted Submatrix Coverage Problem: A CP Approach. In Louis-Martin Rousseau, Kostas Stergiou (ed.), Integration of Constraint Programming, Artificial Intelligence, and Operations Research : Lecture Notes in Computer Science (16th International Conference, CPAIOR 2019, Thessaloniki, Greece, June 4–7, 2019, Proceedings, p. p. 258-274). Springer, Cham. https://doi.org/10.1007/978-3-030-19212-9_17
2018
Papier de conférence
Cappart, Q., Aoga, J., & Schaus, P. (2018). EpisodeSupport: A Global Constraint for Mining Frequent Patterns in a Long Sequence of Events. Lecture Notes in Computer Science, 10848(1), 82-99. https://doi.org/10.1007/978-3-319-93031-2_7 (Original work published 2018)
Verhaeghe, H., Lecoutre, C., & Schaus, P. (2018). Compact-MDD: Efficiently Filtering (s)MDD Constraints with Reversible Sparse Bit-sets. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence. Published. Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}, Stockholm, Sweden. https://doi.org/10.24963/ijcai.2018/192
Thomas, C., & Schaus, P. (2018). Revisiting the self-adaptive large neighborhood search. Lecture Notes in Computer Science, 10848 LNCS(1), 557-566. https://doi.org/10.1007/978-3-319-93031-2_40 (Original work published 2018)
Aoga, J., Guns, T., Nijssen, S., & Schaus, P. (2018). Finding Probabilistic Rule Lists using the Minimum Description Length Principle. Discovery Science 21th International Conference, DS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings. Published. 21st International Conference on Discovery Science (DS 2018), Limassol, Cyprus. (Original work published 2018)
Verhaeghe, H., Lecoutre Christophe, Deville, Y., & Schaus, P. (2018). Extension de Compact-Table aux Tables Simplement Intelligentes. Quatorzième journées Francophones de Programmation par Contraintes (JFPC18), Amiens, France.
Khong, M. T., Lecoutre, C., Schaus, P., & Deville, Y. (2018). Soft-regular with a Prefix-size Violation Measure. Soft-regular with a Prefix-size Violation Measure. Accepted/in-press. 15th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, Delft, The Netherlands. (Original work published 2018)
Cappart, Q., Thomas, C., Schaus, P., & Rousseau, L.-M. (2018). A Constraint Programming Approach for Solving Patient Transportation Problems. Lecture Notes in Computer Science : Principles and Practice of Constraint Programming, p. 490-506. https://doi.org/10.1007/978-3-319-98334-9_32
Chapitre de livre
Branders, V., Schaus, P., & Dupont, P. (2018). Combinatorial Optimization Algorithms to Mine a Sub-Matrix of Maximal Sum. In Annalisa Appice, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras (ed.), New Frontiers in Mining Complex Patterns (6th International Workshop, NFMCP 2017, Held in Conjunction with ECML-PKDD 2017, Macedonia, Sept. 18-22, Revised Selected Papers, p. p. 65-79). https://doi.org/10.1007/978-3-319-78680-3_5
Document de travail
Thu Hien Dao, Docquier, F., Mathilde Maurel, & Schaus, P. (2018). Global Migration in the 20th and 21st Centuries: the Unstoppable Force of Demography (IRES Discussion Papers 2018-3).
Article de journal
Van Cauwelaert, S., Lombardi, M., & Schaus, P. (2018). How efficient is a Global Constraint in Practice ? Constraints : an international journal, 23, 87-122. https://doi.org/10.1007/s10601-017-9277-y (Original work published 2018)
2017
Papier de conférence
Houndji, V. R., Schaus, P., Hounkonnou, M. N., & Wolsey, L. (2017). The weighted arborescence constraint. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformat, 10335 LNCS, 185-201. https://doi.org/10.1007/978-3-319-59776-8_15 (Original work published 2017)
Aoga, J., Guns, T., & Schaus, P. (2017). Algorithme Efficace pour la Fouille de Séquences Fréquentes avec la Programmation par Contraintes. Treizièmes Journées Francophones de Programmation par Contraintes, Montreuil-sur-mer,.
Verhaeghe, H., Lecoutre, C., & Schaus, P. (2017). Extension de Compact-Table aux tables négatives et concises. Treizièmes journées Francophones de Programmation par Contraintes (JFPC17), Montreuil-sur-Mer, France.
Verhaeghe, H., Lecoutre, C., Deville, Y., Schaus, P., & et al. (2017). Extending Compact-Table to Basic Smart Tables. Principles and Practice of Constraint Programming, p. 297-307.
Cappart, Q., Limbrée, C., Schaus, P., Quilbeuf, J., Traonouez, L.-M., & Legay, A. (2017). Verification of Interlocking Systems Using Statistical Model Checking. IEEE International Symposium on High-Assurance Systems Engineering, 2017 IEEE 18th International Symposium on High Assurance Systems Engineering (HASE). https://doi.org/10.1109/HASE.2017.10 (Original work published 2017)
Cappart, Q., & Schaus, P. (2017). Rescheduling Railway Traffic on Real Time Situations Using Time-Interval Variables. Lecture Notes in Computer Science, 10335, 312-327. https://doi.org/10.1007/978-3-319-59776-8_26 (Original work published 2017)
Van Cauwelaert, S., & Schaus, P. (2017). Efficient Filtering for the Resource-Cost AllDifferent Constraint. Fourteenth International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint P, Padova.
Schaus, P., Aoga, J., & Guns, T. (2017). CoverSize: A Global Constraint for Frequency-based Itemset Mining. Lecture Notes in Computer Science, LNCS 10416, 1-18. (Original work published 2017)
Verhaeghe, H., Lecoutre, C., & Schaus, P. (2017). Extending Compact-Table to Negative and Short Tables. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence and the Twenty-Ninth Innovative Applications of Artificial Intelligence Conference, 5. (Original work published 2017)
Branders, V., Schaus, P., & Dupont, P. (2017). Mining a sub-matrix of maximal sum. Proceedings of the 6th International Workshop on New Frontiers in Mining Complex Patterns in conjunction with ECML-PKDD 2017. Published. 6th International Workshop on New Frontiers in Mining Complex Patterns in conjunction with ECML-PKDD 2017, Skopje (MK). (Original work published 2017)
Khong, M. T., Deville, Y., Schaus, P., & Lecoutre, C. (2017). Efficient Reification of Table Constraints. International Conference on Tools with Artificial Intelligence. Proceedings. Published. International Conference on Tools with Artificial Intelligence, Boston, MA, US. (Original work published 2017)
Cappart, Q., Limbrée, C., Schaus, P., Quilbeuf, J., Traonouez, L.-M., & Legay, A. (2017). Verification of Interlocking Systems Using Statistical Model Checking. 2017 IEEE 18th International Symposium on High Assurance Systems Engineering (HASE). Published. 18th IEEE International Symposium on High Assurance Systems Engineering (HASE), Singapore. https://doi.org/10.1109/HASE.2017.10
Article de journal
Aoga, J., Guns, T., & Schaus, P. (2017). Mining Time-constrained Sequential Patterns with Constraint Programming. Constraints : an international journal, 22(3), 1-23. https://doi.org/10.1007/s10601-017-9272-3 (Original work published 2017)
Van Cauwelaert, S., & Schaus, P. (2017). Efficient Filtering for the Resource-Cost AllDifferent Constraint. Constraints : an international journal, 22(4), 493-511. https://doi.org/10.1007/s10601-017-9269-y (Original work published 2017)
Derval, G., Régin, J.-C., & Schaus, P. (2017). Improved filtering for the bin-packing with cardinality constraint. Constraints : an international journal, 23, 251-271. https://doi.org/10.1007/s10601-017-9278-x (Original work published 2018)
2016
Papier de conférence
Van Cauwelaert, S., Dejemeppe, C., Monette, J.-N., & Schaus, P. (2016). Efficient Filtering for the Unary Resource with Family-based Transition Times. International Conference on Principles and Practice of Constraint Programming, Toulouse.
Aoga, J., Guns, T., & Schaus, P. (2016). An Efficient Algorithm for Mining Frequent Sequence with Constraint Programming. In Paolo Frasconi, Niels Landwehr, Giuseppe Manco and Jilles Vreeken (ed.) (ed.), Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II (pp. 315-330). https://doi.org/10.1007/978-3-319-46227-1_20
Palmieri, A., Régin, J.-C., & Schaus, P. (2016). Parallel Strategies Selection. Lecture Notes in Computer Science, 9892(9892), 388-404. https://doi.org/10.48550/arXiv.1604.06484 (Original work published 2016)
Cappart, Q., & Schaus, P. (2016). A Dedicated Algorithm for Verification of Interlocking Systems. Lecture Notes in Computer Science, 9922, 76-87. https://doi.org/10.1007/978-3-319-45477-1_7 (Original work published 2016)
Derval, G., Schaus, P., & et al. (2016). Embarrassingly Parallel Search Reengineered. “Doctoral Program of the 22nd International Conference on Principles and Practice of Constraint Programming (CP 2016)”, Toulouse. Published. Doctoral Program of the 22nd International Conference on Principles and Practice of Constraint Programming (CP 2016), Toulouse, France. (Original work published 2016)
Dejemeppe, C., Devolder, O., Lecomte, V., & Schaus, P. (2016). Forward-Checking Filtering for Nested Cardinality Constraints: Application to an Energy Cost-Aware Production Planning Problem for Tissue Manufacturing. Lecture Notes in Computer Science, 9676(9676), 108-124. https://doi.org/10.1007/978-3-319-33954-2_9 (Original work published 2016)
Demeulenare, J., Hartert, R., Lecoutre, C., Perrez, G., Perron, L., Régin, J.-C., & Schaus, P. (2016). Compact-Table: Efficiently Filtering Table Constraints with Reversible Sparse Bit-Sets. Lecture Notes in Computer Science, 9892(9892), 207-223. https://doi.org/10.48550/arXiv.1604.06641 (Original work published 2016)
Document de travail
Cappart, Q., Limbrée, C., Schaus, P., Quilbeuf, J., Traonouez, L.-M., & Legay, A. (2016). Verification of interlocking systems using statistical model checking.
2015
Papier de conférence
Van Cauwelaert, S., Dejemeppe, C., & Schaus, P. (2015). The Unary Resource with Transition Times. Lecture Notes in Computer Science. Published. Principles and Practice of Constraint Programming. https://doi.org/10.1007/978-3-319-23219-5_7
Gay, S., Hartert, R., Schaus, P., & et al. (2015). Conflict Ordering Search for Scheduling Problems. Lecture Notes in Computer Science. Published. Principles and Practice of Constraint Programming, Cork Ireland. https://doi.org/10.1007/978-3-319-23219-5_10
Gay, S., Hartert, R., & Schaus, P. (2015). Simple and Scalable Time-Table Filtering for the Cumulative Constraint. Lecture Notes in Computer Science. Published. Principles and Practice of Constraint Programming, Cork Ireland. https://doi.org/10.1007/978-3-319-23219-5_11
Cappart, Q., Schaus, P., Limbrée, C., & et al. (2015). Verification by discrete simulation of interlocking systems. 29th European Simulation and Modelling Conference, Leicester, UK.
Hartert, R., Schaus, P., Vissicchio, S., & Bonaventure, O. (2015). Solving Segment Routing Problems with Hybrid Constraint Programming Techniques. Proceedings of CP 2015. Published. International Conference on Principles and Practice of Constraint Programming (CP), Cork, Ireland. https://doi.org/10.1007/978-3-319-23219-5_41
Hartert, R., Gay, S., & Schaus, P. (2015). Time-Table Disjunctive Reasoning for the Cumulative Constraint. Lecture Notes in Computer Science. Published. Integration of AI and OR Techniques in Constraint Programming, Barcelona. https://doi.org/10.1007/978-3-319-18008-3_11
Van Cauwelaert, S., Schaus, P., & et al. (2015). Understanding the Potential of Propagators. Lecture Notes in Computer Science, p. pp 427-436. https://doi.org/10.1007/978-3-319-18008-3_29
Hartert, R., Vissicchio, S., Schaus, P., Bonaventure, O., Filsfils, C., Telkamp, T., & Francois, P. (2015). A Declarative and Expressive Approach to Control Forwarding Paths in Carrier-Grade Networks. Proceedings of SIGCOMM 2015. Published. 28th Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM) on the applications, technologies, architectures, and protocols for computer communication, London. https://doi.org/10.1145/2785956.2787495
Deville, Y., Dejemeppe, C., & Schaus, P. (2015). Derivative-Free Optimization: Lifting Single-Objective to Multi-Objective Algorithm. Lecture Notes in Computer Science, 9075(9075), 124-140. https://doi.org/10.1007/978-3-319-18008-3_9 (Original work published 2015)
Busard, S., Cappart, Q., Limbrée, C., Pecheur, C., & Schaus, P. (2015). Verification of railway interlocking systems. Electronic Proceedings in Theoretical Computer Science, 184, 19-31. https://doi.org/10.4204/EPTCS.184.2 (Original work published 2015)
2014
Papier de conférence
Hartert, R., & Schaus, P. (2014). A Support-Based Propagator for the Bi-Objective Pareto Constraint. The Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14), Québec.
Lombardi, M., & Schaus, P. (2014). Cost impact guided LNS. International Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, Cork, Ireland. https://doi.org/10.1007/978-3-319-07046-9_21
Van Cauwelaert, S., Lombardi, M., & Schaus, P. (2014). Supervised Learning to Control Energetic Reasoning: A Feasibility Study.
Houndji, V. R., Schaus, P., Wolsey, L., & Deville, Y. (2014). The Stocking Cost Constraint. International Conference on Principles and Practice of Constraint Programming (CP2014), Lyon.
Gay, S., & Schaus, P. (2014). Continuous Casting Scheduling with Constraint Programming. International Conference on Principles and Practice of Constraint Programming (CP2014), Lyon, France.
Article de journal
Schaus, P., & Régin, J.-C. (2014). Bound-consistent spread constraint : application to load balancing in nurse-to-patient assignments. EURO Journal on Computational Optimization, 2(3), 123-146. https://doi.org/10.1007/s13675-013-0018-8 (Original work published 2013)
2013
Papier de conférence
Schaus, P. (2013). Variable objective large neighborhood search: a practical approach to solve over-constrained problems. IEEE International Conference on Tools with Artificial Intelligence (ICTAI) - 2013, Washington DC, USA.
le Clément de Saint-Marcq, V., Schaus, P., Solnon, C., & Lecoutre, C. (2013). Sparse-sets for domain implementation. The 19th International Conference on Principles and Practice of Constraint Programming, Uppsala, Sweden.
Pelsser, F., Schaus, P., & Regin, J.-C. (2013). Revisiting the cardinality reasoning for BinPacking constraint. Principles and Practice of Constraint Programming, p. 578-586. https://doi.org/10.1007/978-3-642-40627-0_43
Schaus, P., & Hartert, R. (2013). Multi-objective large neighborhood search. Principles and Practice of Constraint Programming, 611-627. https://doi.org/10.1007/978-3-642-40627-0_46
Article de journal
Schaus, P., & Régin, J.-C. (2013). Bound-consistent spread constraint. EURO Journal on Computational Optimization. Accepted/in-press. (Original work published 2013)
2012
Papier de conférence
Schaus, P., & et al. (2012). Cardinality Reasoning for bin-packing constraint. Application to a tank allocation problem. In Pierre Schaus, Jean-Charles Régin, Rowan Van Schaeren, Wout Dullaert, Birger Raa (ed.), Principles and Practice of Constraint Programming - 18th International Conference (pp. 815-822). Springer, LNCS. https://doi.org/10.1007/978-3-642-33558-7
2010
Papier de conférence
Dupuis, J., Schaus, P., & Deville, Y. (2010). Vérification de consistence pour la constrainte de bin packing. Sixièmes journées Francophones de programmation par contraintes (JFPC 2010), Caen, France.
Mairy, J.-B., Schaus, P., & Deville, Y. (2010). Generic adaptive heuristics for large neighborhood search. International conference on principles and practice of constraint programming, St Andrews, Scotland.
Schaus, P., Van Hentenryck, P., & Zanarini, A. (2010). Revisiting the soft global cardinality constraint. Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, p. 307-312. https://doi.org/10.1007/978-3-642-13520-0_33
Dupuis, J., Schaus, P., & Deville, Y. (2010). Consistency Check for the Bin Packing Constraint Revisited. In Lodi, A.; Milano, M.; Toth, P.; (ed.), Integration of AI and OR Techniques in Constraint Programming for Cominatorial Optimization Problems. 7th International Conference, CPAIOR 2010 (p. p. 117-122). Springer. https://doi.org/10.1007/978-3-642-13520-0_15
Schaus, P., Van Hentenryck, P., Monette, J.-N., Coffrin, C., Michel, L., & Deville, Y. (2010). Solving steel mill slab problems with constraint-based techniques: CP, LNS, and CBLS. Constraints : an international journal, 16(2), 125-147. https://doi.org/10.1007/s10601-010-9100-5 (Original work published 2011)
2009
Papier de conférence
Schaus, P., Van Hentenryck, P., & Regin, J.-C. (2009). Scalable Load Balancing in Nurse to Patient Assignment Problems. Lecture Notes in Computer Science, 5547, 248-262. https://doi.org/10.1007/978-3-642-01929-6_19 (Original work published 2009)
Thèse
Schaus, P. (2009). Solving balancing and bin-packing problems with constraint programming.
2008
Papier de conférence
Schaus, P., & Deville, Y. (2008). A Global Constraint for Bin-Packing with Precedences: Application to the Assembly Line Balancing Problem. AAAI-08, Twenty-Third AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, Chicago, USA.
Schaus, P., & Deville, Y. (2008). Hybridization of CP and VLNS for Eternity II. JFPC′08 Quatrième Journées Francophones de Programmation par Contraintes, Nantes, France.
Schaus, P., & Deville, Y. (2008). Une contrainte globale de bin-packing avec précédences: Application au problème d’équilibrage de lignes d’assemblage. Journées Francophones de Programmation par Contraintes (JFPC′08), Nantes, France.
Schaus, P., & Deville, Y. (2008). Global Constraints for the Mean Absolute Deviation and the Variance: Application to the Vertical Line Balancing. 22nd national conference of the Belgian Operations Research Society, Brussels, Belgium.
Schaus, P., & Deville, Y. (2008). Hybridation de la programmation par contraintes et d’un voisinage à très grande taille pour Eternity II. Journées Francophones de Programmation par Contraintes (JFPC′08), Nantes, France.
2007
Chapitre de livre
Schaus, P., Deville, Y., & Dupont, P. (2007). Bound-Consistent Deviation Constraint. In Bessiere, Christian (ed.), Principles and Practice of Constraint Programming, CP 2007 (p. p. 620-634). Springer.
Schaus, P., Deville, Y., Dupont, P., & Regin, J.-C. (2007). Simplification and extension of the SPREAD Constraint. In Benhamou, Frédéric; Jussien, Narendra; O’Sullivan, Barry (Ed. by) (ed.), Trends in Constraint Programming (p. p. 95-99).
Papier de conférence
Deville, Y., Dupont, P., Dooms, G., Monette, J.-N., Schaus, P., Zampelli, S., & Wodak, S. (2007). BioEdge: a tool box for advanced analyses of biochemical networks. Benelux Bioinformatics Conference (BBC′07), Leuven, Belgium.
Schaus, P., Deville, Y., Dupont, P., & Régin, J.-C. (2007). Simplification and extension of the SPREAD Constraint. Third international workshop on constraint propagation and implementation, Nantes, France.
Schaus, P., Deville, Y., Dupont, P., & Regin, J.-C. (2007). The deviation constraint. In Van Hentenryck, P.; Wolsey, L.; (ed.), Integration of AI and OR Techniques in Constraint Programming forCombinatorial Optimization Problems. Proceedings 4th InternationalConference, CPAIOR 2007 (p. p. 260-274). Springer.
Schaus, P., Deville, Y., Dupont, P., & Régin, J.-C. (2007). La Contrainte Déviation. Journées Francophones de Programmation par Contraintes (JFPC′07), Rocquencourt, France.
Monette, J.-N., Schaus, P., Zampelli, S., Deville, Y., & Dupont, P. (2007). A CP Approach to the Balanced Academic Curriculum Problem. Symcon′07, The Seventh International Workshop on Symmetry and Constraint Satisfaction Problems, Providence, USA.
2006
Papier de conférence
Schaus, P., Deville, Y., Dupont, P., & Régin, J.-C. (2006). Simplification and extension of the SPREAD Constraint. Third International Workshop on Constraint Propagation And Implementation (CPAI′06), Nantes, France.