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

A method is given for maximizing a linear function subject to a quadratic and a number of linear constraints. The method differs from general convex programming methods by terminating in a finite ...

This note deals with the manner in which dynamic problems, involving probabilistic constraints, may be tackled using the ideas of Lagrange multipliers and efficient solutions. Both the infinite and ...