We will also review minqp subpackage which is used to solve constrained quadratic programming problems. This article discusses these solvers and their properties. Which are more precise and robust that general ones.ĪLGLIB package provides several state-of-the-art QP solvers which can solveĬonvex and non-convex problems, dense and sparse, box-constrained and linearly constrained ones. However, because we know that function being optimized is quadratic one, we can use specialized optimization algorithms Quadratic programming problems can be solved as general constrained nonlinear optimization problems. Subject to optional boundary and/or general linear equality/inequality constraints: Quadratic programming is a subfield of nonlinear optimization which deals with quadratic optimization problems ALGLIB User Guide - Optimization (nonlinear and quadratic) - Constrained quadratic programming with box/linear constraints
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