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

Abstract: Constraint Answer Set Programming (CASP) combines Answer Set Programming (ASP) and Constraint Programming (CP) to offer a powerful framework for solving complex problems. While there exists ...

Constraint programming (CP) is a programming paradigm where relations between variables are stated in the form of constraints. It's particularly useful for solving complex combinatorial problems such ...

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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 ...

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Track placement – Straights, curves, and switches are modeled with finite-domain variables that encode both geometry and orientation. Capacity constraints ensure no two trains attempt to occupy the ...

Constraint models have been extremely useful in identifying the deleterious variants that underlie disease in the part of the genome in the cell nucleus. However, nuclear constraint models could not ...

This is a preview. Log in through your library . Abstract The hyperbolic (or fractional) linear programming problem with only one aggregate constraint is solved by a simple and extremely efficient ...