Constraint Programming (CP) has been successful in a number of combinatorial search and discrete optimisation problems. Yet other more traditional approaches, such as Integer Programming (IP), can ...

Constraint programming combined with machine learning provides a robust framework for addressing complex combinatorial problems across diverse domains such as energy management, production scheduling ...

Constraints are placed on the level of annual negative deviations in a MOTAD-type firm risk model. Through such arbitrary limits the model selects activities to limit disaster occurrences for each and ...