Towards relational modelling of combinatorial optimisation problems

A high-level abstract-datatype-based constraint modelling language opens the door to an automat-able empirical determination — by a compiler — of how to ‘best ’ represent the variables of a com-binatorial optimisation problem, based on (real-life) training instances of the problem. In the ex-treme case where no such training instances are provided, such a compiler would simply be non-deterministic. A first-order relational calculus with sets is a good candidate for such a language, as it gives rise to very natural and easy-to-maintain models of combinatorial optimisation problems.