Pierre Schaus
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Sequence Variables: A Constraint Programming Computational Domain for Routing and Sequencing Open
Constraint Programming (CP) offers an intuitive, declarative framework for modeling Vehicle Routing Problems (VRP), yet classical CP models based on successor variables cannot always deal with optional visits or insertion based heuristics.…
CP-Model-Zoo: A Natural Language Query System for Constraint Programming Models Open
Constraint Programming and its high-level modeling languages have long been recognized for their potential to achieve the holy grail of problem-solving. However, the complexity of modeling languages, the large number of global constraints,…
A Generic Complete Anytime Beam Search for Optimal Decision Tree Open
Finding an optimal decision tree that minimizes classification error is known to be NP-hard. While exact algorithms based on MILP, CP, SAT, or dynamic programming guarantee optimality, they often suffer from poor anytime behavior -- meanin…
Implementing Cumulative Functions with Generalized Cumulative Constraints Open
Modeling scheduling problems with conditional time intervals and cumulative functions has become a common approach when using modern commercial constraint programming solvers. This paradigm enables the modeling of a wide range of schedulin…
Decision Diagram-Based Branch-and-Bound with Caching for Dominance and Suboptimality Detection Open
The branch-and-bound algorithm based on decision diagrams is a framework for solving discrete optimization problems with a dynamic programming formulation. It works by compiling a series of bounded-width decision diagrams that can provide …
Boosting Decision Diagram-Based Branch-And-Bound by Pre-Solving with Aggregate Dynamic Programming Open
Discrete optimization problems expressible as dynamic programs can be solved by branch-and-bound with decision diagrams. This approach dynamically compiles bounded-width decision diagrams to derive both lower and upper bounds on unexplored…
A Conflict Avoidance Table for Continuous Conflict-Based Search (Extended Abstract) Open
Conflict-Based Search is a state-of-the-art algorithm solving the Multi-Agent Path Finding problem. Given multiple agents with start and goal locations, the problem is to find a set of collision-free paths of minimal cost. Continuous Confl…
Large Neighborhood Search with Decision Diagrams Open
Local search is a popular technique to solve combinatorial optimization problems efficiently. To escape local minima one generally uses metaheuristics or try to design large neighborhoods around the current best solution. A somewhat more b…
Are Travel Bans the Answer to Stopping the Spread of COVID-19 Variants? Lessons from a Multi-Country SIR Model Open
Background: Detections of mutations of the SARS-CoV-2 virus gave rise to new packages of interventions. Among them, international travel restrictions have been one of the fastest and most visible responses to limit the spread of the varian…
Are Travel Bans the Answer to Stopping the Spread of COVID-19 Variants? Lessons from a Multi-Country SIR Model Open
Detections of mutations of the SARS-CoV-2 virus gave rise to new packages of interventions. Among them, international travel restrictions have been one of the fastest and most visible responses to limit the spread of the variants. While in…
Assessing Optimal Forests of Decision Trees Open
The interest in algorithms for learning optimal decision trees (ODTs) has increased significantly in recent years. These algorithms use combinatorial search to find a predictive machine learning model in the form of a tree. It was shown th…
Cross-Border Mobility Responses to Covid-19 in Europe: New Evidence from Facebook Data Open
BackgroundWe use a unique database on Facebook users’ mobility to study the daily evolution of cross-border movements of people during the Covid-19 pandemic. To limit censoring issues, we focus on 45 pairs of European countries, and docume…
View article: Improving the filtering of Branch-And-Bound MDD solver (extended)
Improving the filtering of Branch-And-Bound MDD solver (extended) Open
This paper presents and evaluates two pruning techniques to reinforce the efficiency of constraint optimization solvers based on multi-valued decision-diagrams (MDD). It adopts the branch-and-bound framework proposed by Bergman et al. in 2…
Generic Constraint-based Block Modeling using Constraint Programming Open
Block modeling has been used extensively in many domains including social science, spatial temporal data analysis and even medical imaging. Original formulations of the problem modeled it as a mixed integer programming problem, but were no…
Generic Constraint-based Block Modeling using Constraint Programming Open
Block modeling has been used extensively in many domains including social science, spatial temporal data analysis and even medical imaging. Original formulations of the problem modeled it as a mixed integer programming problem, but were no…
Software Open Access Maximal-Sum Submatrix search using a hybrid Contraint Programming/Linear Programming approach: experiment code and results Open
Experiments (made with Snakemake) code & results for the paper " Software Open Access Maximal-Sum Submatrix search using a hybrid Contraint Programming/Linear Programming approach" under review at EJOR.