Constraint programming (CP) is a powerful paradigm for solving combinatorial problems. However, finding well-structured problems and solutions can be challenging, especially for beginners. This ...

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

A popular example would be Soduko, to solve a Soduko with constraint programming you feed the rules (all numbers in each row must be distinct etc) to the solver, which then searches for a solution ...

In this paper we consider the bilevel programming problem (BLPP), which is a sequence of two optimization problems where the constraint region of the upper-level problem is determined implicitly by ...

CAMUS should be able to build on any operating system, though it has only been tested on Linux. It is implemented in the Go programming language (which can be installed here). There are three methods ...

The hyperbolic (or fractional) linear programming problem with only one aggregate constraint is solved by a simple and extremely efficient algorithm. The core step in the iterative procedure is the ...

Example 8.10: Quadratic Programming The quadratic program can be solved by solving an equivalent linear complementarity problem when H is positive semidefinite. The approach is outlined in the ...