Paper accepted at CPAIOR 2020
The work generalizes ideas from core-guided maximum satisfiability to more general finite-domain constraint optimization.

Core-Guided and Core-Boosted Search for CP, co-authored by Jeremias Berg (Constraint Reasoning and Optimization Group) together with Graeme Grange,  Emir Demirovic, and Peter Stuckey (University of Melbourne, Australia), has been accepted for publication in the proceedings of the 17th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2020).

The paper studies generalizations of core-guided search techniques from maximum satisfiability (MaxSAT) to more general finite-domain constraint optimization (CP). The authors show that CP allow designing core-guided transformations that are more effective than straight-forward liftings of the transformations used by core guided MaxSAT solvers. Furthermore, the work generalizes the more recently proposed core-boosted search strategy to CP and shows that combining the CP specific core transformations with branch-and-bound search, results in a state-of-the-art approach to exact optimization in constraint programming.