4 citations · 7 across the 6 of their papers we have counts for
8 papers
Translating finite-domain integer constraint models to CP/SMT/ILP/PB/SAT solvers with CPMpy
Tias Guns, Ignace Bleukx, Hendrik Bierlee +8
Constraint solving is a declarative approach for solving combinatorial satisfaction and optimization problems. The user specifies their problem through constraints and decision var…
LLM-Guided Evolutionary Search for Constraint Model Reformulation to Improve Solver Efficiency
Kostis Michailidis, Dimos Tsouros, Nguyen Dang +1
Combinatorial problems appear in numerous industrial applications. A common approach is to formulate these problems as declarative constraint models that can subsequently be compil…
DCP-Bench-Open: Evaluating LLMs for Constraint Modelling of Discrete Combinatorial Problems
Kostis Michailidis, Dimos Tsouros, Tias Guns
Discrete Combinatorial Problems (DCPs) are prevalent in industrial decision-making and optimisation. However, while constraint solving technologies for DCPs have advanced significa…
Solver-Free Decision-Focused Learning for Linear Optimization Problems
Senne Berden, Ali İrfan Mahmutoğulları, Dimos Tsouros +1
Mathematical optimization is a fundamental tool for decision-making in a wide range of applications. However, in many real-world scenarios, the parameters of the optimization probl…
Generalizing Constraint Models in Constraint Acquisition
Dimos Tsouros, Senne Berden, Steven Prestwich +1
Constraint Acquisition (CA) aims to widen the use of constraint programming by assisting users in the modeling process. However, most CA methods suffer from a significant drawback:…
Trustworthy and Explainable Decision-Making for Workforce allocation
Guillaume Povéda, Ryma Boumazouza, Andreas Strahl +7
In industrial contexts, effective workforce allocation is crucial for operational efficiency. This paper presents an ongoing project focused on developing a decision-making tool de…
Learning to Learn in Interactive Constraint Acquisition
Dimos Tsouros, Senne Berden, Tias Guns
Constraint Programming (CP) has been successfully used to model and solve complex combinatorial problems. However, modeling is often not trivial and requires expertise, which is a…
Holy Grail 2.0: From Natural Language to Constraint Models
Dimos Tsouros, Hélène Verhaeghe, Serdar Kadıoğlu +1
Twenty-seven years ago, E. Freuder highlighted that "Constraint programming represents one of the closest approaches computer science has yet made to the Holy Grail of programming:…