Extensible Automated Constraint Modelling

In constraint solving, a critical bottleneck is the formulation of an effective constraint model of a given problem. The CONJURE system described in this paper, a substantial step forward over prototype versions of CONJURE previously reported, makes a valuable contribution to the automation of constraint modelling by automatically producing constraint models from their specifications in the abstract constraint specification language ESSENCE. A set of rules is used to re- fine an abstract specification into a concrete constraint model. We demonstrate that this set of rules is readily extensible to increase the space of possible constraint models CONJURE can produce. Our empirical results confirm that CONJURE can reproduce successfully the kernels of the constraint models of 32 benchmark problems found in the literature.

Authors

• Ozgur Akgun University of St. Andrews
• Ian Miguel University of St Andrews
• Chris Jefferson University of St. Andrews
• Alan Frisch University of York
• Brahim Hnich Izmir University of Economics

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