Search Results

Documents authored by Lazaar, Nadjib

Artifact
Software
DOI: 10.4230/artifacts.26906
Peak-Utility Using CP

Authors: Chaima Hamdi, Nadjib Lazaar, Nassim Belmecheri, Djawad Bekkoucha, Said Jabbour, and Lakhdar Saïs

Abstract
Cite as

Chaima Hamdi, Nadjib Lazaar, Nassim Belmecheri, Djawad Bekkoucha, Said Jabbour, Lakhdar Saïs. Peak-Utility Using CP (Software). Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@misc{dagstuhl-artifact-26906,
   title = {{Peak-Utility Using CP}}, 
   author = {Hamdi, Chaima and Lazaar, Nadjib and Belmecheri, Nassim and Bekkoucha, Djawad and Jabbour, Said and Sa\"{i}s, Lakhdar},
   note = {Software, swhId: \href{https://archive.softwareheritage.org/swh:1:dir:0537fa0fd6f91dd5f7ed23d393bea3d15fa4d0fd;origin=https://gitlab.lisn.upsaclay.fr/dpm/peakutility;visit=swh:1:snp:2bf6143c24e9d95716a7f862397ac25c22afb6cb;anchor=swh:1:rev:9a5a4da55a1f9c6f61bd5df4ad5592675377d6a6}{\texttt{swh:1:dir:0537fa0fd6f91dd5f7ed23d393bea3d15fa4d0fd}} (visited on 2026-07-13)},
   url = {https://gitlab.lisn.upsaclay.fr/dpm/peakutility.git},
   doi = {10.4230/artifacts.26906},
}
Document
DOI: 10.4230/LIPIcs.CP.2026.4
ScenaGen: A CP Model for Grounding Qualitative Driving Scenarios

Authors: Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar, and Helge Spieker

Published in: LIPIcs, Volume 379, 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026)

Abstract
Validating Automated Driving Systems (ADS) requires generating various kinematically executable traffic scenarios. The grounding of qualitative descriptions into concrete trajectories is a combinatorial task poorly addressed by learning-based methods. We propose ScenaGen, a CP model operating on qualitative explainable graphs (QXGs) to encode spatio-temporal relations between traffic entities. Formulated over integer position variables, ScenaGen enforces qualitative spatial constraints, distance thresholds, and inter-frame kinematic consistency. A single QXG acts as a formal template for systematically enumerating distinct, quantitatively varied concrete scenarios. Evaluation of synthetic and real-world benchmarks demonstrates that ScenaGen provides a robust and efficient alternative for scenario instantiation, outperforming standard search baselines in both scalability and solution diversity.
Cite as

Nassim Belmecheri, Arnaud Gotlieb, Nadjib Lazaar, and Helge Spieker. ScenaGen: A CP Model for Grounding Qualitative Driving Scenarios. In 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 379, pp. 4:1-4:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@InProceedings{belmecheri_et_al:LIPIcs.CP.2026.4,
  author =	{Belmecheri, Nassim and Gotlieb, Arnaud and Lazaar, Nadjib and Spieker, Helge},
  title =	{{ScenaGen: A CP Model for Grounding Qualitative Driving Scenarios}},
  booktitle =	{32nd International Conference on Principles and Practice of Constraint Programming (CP 2026)},
  pages =	{4:1--4:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-432-1},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{379},
  editor =	{Beldiceanu, Nicolas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2026.4},
  URN =		{urn:nbn:de:0030-drops-266378},
  doi =		{10.4230/LIPIcs.CP.2026.4},
  annote =	{Keywords: Constraint Programming, Scenario Grounding, Qualitative Reasoning, Autonomous Driving, Application}
}
Document
DOI: 10.4230/LIPIcs.CP.2026.27
Utility-Peak Itemset Mining with Constraint Programming

Authors: Chaima Hamdi, Nadjib Lazaar, Nassim Belmecheri, Djawad Bekkoucha, Said Jabbour, and Lakhdar Saïs

Published in: LIPIcs, Volume 379, 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026)

Abstract
High-Utility Itemset Mining (HUIM) aims to discover itemsets whose utility exceeds a given threshold. While specialized algorithms achieve strong performance, they lack flexibility when additional domain constraints must be incorporated. Constraint Programming (CP) offers a declarative alternative, but requires strong propagation to remain competitive. In this paper, we propose a CP framework for utility-driven pattern mining based on a parameterized global constraint that unifies the enumeration of High-Utility Itemsets (HUIs) and a new condensed representation called Utility-Peak Itemsets (UPIs). A UPI is an itemset whose utility is greater or equal than that of all its immediate subsets and supersets, capturing locally utility-maximal patterns. We study the computational complexity of UPI mining and show that deciding whether a high-utility UPI exists, for a given utility threshold, is NP-complete. Our global constraint, PeakUtility, integrates utility computation and upper-bound pruning through propagation rules. Experiments demonstrate that our approach performs competitively with the state of the art HUIM algorithms while preserving the modelling flexibility of CP.
Cite as

Chaima Hamdi, Nadjib Lazaar, Nassim Belmecheri, Djawad Bekkoucha, Said Jabbour, and Lakhdar Saïs. Utility-Peak Itemset Mining with Constraint Programming. In 32nd International Conference on Principles and Practice of Constraint Programming (CP 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 379, pp. 27:1-27:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

Copy BibTex To Clipboard

@InProceedings{hamdi_et_al:LIPIcs.CP.2026.27,
  author =	{Hamdi, Chaima and Lazaar, Nadjib and Belmecheri, Nassim and Bekkoucha, Djawad and Jabbour, Said and Sa\"{i}s, Lakhdar},
  title =	{{Utility-Peak Itemset Mining with Constraint Programming}},
  booktitle =	{32nd International Conference on Principles and Practice of Constraint Programming (CP 2026)},
  pages =	{27:1--27:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-432-1},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{379},
  editor =	{Beldiceanu, Nicolas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2026.27},
  URN =		{urn:nbn:de:0030-drops-266595},
  doi =		{10.4230/LIPIcs.CP.2026.27},
  annote =	{Keywords: Constraint Programming, Pattern Mining, HUI Mining, Global Constraints, Declarative Data Mining}
}
Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2026 Schloss Dagstuhl – LZI GmbH Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact