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 …

Optimization problems are pervasive in sectors from manufacturing and distribution to
healthcare. However, most such problems are still solved heuristically by hand rather than …

Constraint modelling is widely recognised as a key bottleneck in applying constraint solving
to a problem of interest. The Conjure automated constraint modelling system addresses this …

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

Research in constraint programming typically focuses on problem solving efficiency.
However, the way users conceptualise problems and communicate with constraint …

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

Modeling in constraint programming is a hard task that requires considerable expertise.
Automated model reformulation aims at assisting a naive user in modeling constraint …

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 …