Lazy Clause Generation (LCG) solvers dominate the current constraint programming competitions. These solvers successfully combine systematic propagation based search, global constraints and conflict clause learning from SAT solving into a hybrid approach. My research project extends the LCG methodology by using a mix of eager and lazy encodings and a richer set of constraint decompositions. Glo...

This paper considers Just-In-Time Job-Shop Scheduling, in which each activity has an earliness and a tardiness cost with respect to a due date. It proposes a constraint programming approach, which includes a novel filtering algorithm and dedicated heuristics. The filtering algorithm uses a machine relaxation to produce a lower bound that can be obtained by solving a Just-In-Time Pert problem. I...

The Algebraic Dichotomy Conjecture states that the Constraint Satisfaction Problem over a fixed template is solvable in polynomial time if the algebra of polymorphisms associated to the template lies in a Taylor variety, and is NP-complete otherwise. This paper provides two new characterizations of finitely generated Taylor varieties. The first characterization is using absorbing subalgebras an...

Pseudonymization is a promising technique for publishing a trajectory location data set in a privacy-preserving way. However, it is not trivial to determine whether a given data set is safely publishable against an adversary with partial knowledge about users’ movements. We therefore formulate this safety decision problem based on the framework of constraint satisfaction problems (CSPs) and eva...

Broken triangles constitute an important concept not only for solving constraint satisfaction problems in polynomial time, but also for variable elimination or domain reduction by merging domain values. Specifically, for a given variable in a binary arc-consistent CSP, if no broken triangle occurs on any pair of values, then this variable can be eliminated while preserving satisfiability. More ...

This paper describes new algorithms for processing quantitative and qualitative Temporal Constraint Satisfaction Problems (TCSP). In contrast to discrete Constraint Satisfaction Problems (CSP), enforcing path-consistency on quantitative TCSP is exponential, due to the fragmentation problem. Identifying the fragmentation problem allows us to design several e cient polynomial algorithms that are ...

Maximum surjective constraint satisfaction problems (Max-SurCSPs) are computational problems where we are given a set of variables denoting values from a finite domain B and a set of constraints on the variables. A solution to such a problem is a surjective mapping from the set of variables to B such that the number of satisfied constraints is maximized. We study the approximation performance t...

Several variants of the Constraint Satisfaction Problem have been proposed and investigated in the literature for modelling those scenarios where solutions are associated with some given costs. Within these frameworks computing an optimal solution is an NP-hard problem in general; yet, when restricted over classes of instances whose constraint interactions can be modelled via (nearly-)acyclic g...

We study the concept of propagation connectivity on random 3-uniform hypergraphs. This concept is inspired by a simple linear time algorithm for solving instances of certain constraint satisfaction problems. We derive upper and lower bounds for the propagation connectivity threshold, and point out some algorithmic implications.

Symmetry breaking has been shown to be an important method to speed up the search in constraint satisfaction problems that contain symmetry. When breaking symmetry by dominance detection, a computationally efficient symmetry breaking scheme can be achieved if we can solve the dominance detection problem in polynomial time. We study the complexity of dominance detection when value and variable s...