Constraint logic programming (CLP) was a revolution in declarative programming showing how we could answer very interesting and complex questions by a combination of programmed search and constraint solving. But constraint programming (CP) moved away from its logic programming roots to concentrate on modelling, simply specifying a system of constraints, in the process losing the ability to do complex meta-search. MiniZinc is one of the leading constraint programming modelling languages. It was originally designed to tackle complex CP problems, typically small systems of complex constraints. But its uses have changed, often it is used to solve very large systems of simple constraints. This meant that many of the original assumptions in the design of MiniZinc are invalid. In this talk we will examine a new architecture for MiniZinc, which uses constraint solving for model optimization, and includes incremental solving and backtracking. In some sense the new architecture makes MiniZinc a CLP system, bringing us back to the roots of the field.

This is joint work with Guido Tack, Graeme Gange, and Jip Dekker.