As multi-core computing is now standard, it seems irresponsible for constraints researchers
to ignore the implications of it. Researchers need to address a number of issues to exploit …

When solving a combinatorial problem, the formulation or model of the problem is critical to
the efficiency of the solver. Automating the modelling process has long been of interest …

MiniZinc is a modelling language for combinatorial problems, which can then be solved by a
solver provided in a backend. There are many backends, based on technologies such as …

Constraint Programming (CP) is a powerful technique for solving large-scale combinatorial
problems. Solving a problem proceeds in two distinct phases: modelling and solving …

In this paper, we present a summary of XCSP 3, together with its ecosystem. XCSP 3 is a
format used to build integrated representations of combinatorial constrained problems …

We describe a system which generates finite domain constraint models from positive
example solutions, for highly structured problems. The system is based on the global …

Access to good benchmark instances is always desirable when develo** new algorithms,
new constraint models, or when comparing existing ones. Hand-written instances are of …

Constraint Programming (CP) is a powerful technique for solving large-scale combinatorial
(optimisation) problems. Constraint solving a given problem proceeds in two phases …

Many constraint problems contain symmetry, which can lead to redundant search. If a partial
assignment is shown to be invalid, we are wasting time if we ever consider a symmetric …

Structured Neighbourhood Search (SNS) is a framework for constraint-based local search
for problems expressed in the Essence abstract constraint specification language. The local …