Optimising Quantified Expressions in the Automated Constraint Modelling Tool TAILOR

Constraint Programming (CP) is a powerful technique for solving large-scale combinatorial (optimisation) problems. However, CP is often inaccessible to users without expert knowledge in the area, precluding its widespread use. One of the key difficulties lies in formulating an effective constraint model of an input problem for input to a constraint solver. Automated Constraint Modelling tools address this issue by providing assistance in model formulation. TAILOR is one such modelling tool. It incorporates a number of highly effective model optimisations, which can compensate for a wide selection of poor modelling choices that novices (but also experts) often make. In the context of TAILOR, this paper presents new constraint model optimisation techniques concerned with optimising quantified expressions, constructs that are commonly used in high-level constraint modelling languages, similar to for-loops in programming languages. Our experimental results show that quantified expression optimisations can reduce solving time very considerably.