Learn More
There is no standard modelling language for constraint programming (CP) problems. Most solvers have their own modelling language. This makes it difficult for modellers to experiment with different solvers for a problem. In this paper we present MiniZinc, a simple but expressive CP modelling language which is suitable for modelling problems for a range of(More)
We present Alice, a functional programming language that has been designed with strong support for typed open programming. It incorporates concurrency with data flow synchronisation, higher-order modularity, dynamic modules, and type-safe pickling as a minimal and generic set of simple, orthogonal features providing that support. Based on these mechanisms(More)
Today’s models for propagation-based constraint solvers require propagators as implementations of constraints to be at least contracting and monotonic. These models do not comply with reality: today’s constraint programming systems actually use non-monotonic propagators. This paper introduces the first realistic model of constraint propagation by assuming a(More)
set of MiniZinc models and problems instances. MiniZinc1 (Nethercote et al. 2007) was our response to the call for a standard constraint-programming modeling language. MiniZinc is high level enough to express most combinatorial optimization problems easily and in a largely solverindependent way; for example, it supports sets, arrays, and user-defined(More)
We present Alice, a functional programming language that has been designed with strong support for typed open programming. It incorporates concurrency with data flow synchronisation, higher-order modularity, dynamic modules, and type-safe pickling as a minimal and generic set of simple, orthogonal features providing that support. Based on these mechanisms(More)
The ability to model search in a constraint solver can be an essential asset for solving combinatorial problems. However, existing infrastructure for defining search heuristics is often inadequate. Either modeling capabilities are extremely limited or users are faced with a general-purpose programming language whose features are not tailored towards writing(More)
We introduce MiningZinc, a general framework for constraint-based pattern mining, one of the most popular tasks in data mining. MiningZinc consists of two key components: a language component and a toolchain component. The language allows for high-level and natural modeling of mining problems, such that MiningZinc models closely resemble definitions found(More)
Much of the power of CP comes from the ability to create complex hybrid search algorithms specific to an application. Unfortunately there is no widely accepted standard for specifying search, and each solver typically requires detailed knowledge in order to build complex searches. This makes the barrier to entry for exploring different search methods quite(More)
Functional relations are ubiquitous in combinatorial problems – the Global Constraint Catalog lists 120 functional constraints. This paper argues that the ability to express functional constraints with functional syntax leads to more elegant and readable models, and that it enables a better translation of the models to different underlying solving(More)