A Primal-Dual Active-Set Method for Convex Quadratic Programming
نویسندگان
چکیده
The paper deals with a method for solving general convex quadratic programming problems with equality and inequality constraints. The interest in such problems comes from at least two facts. First, quadratic models are widely used in real-life applications. Second, in many algorithms for nonlinear programming, a search direction is determined at each iteration as a solution of a quadratic problem. The method uses information about dual and primal variables to effectively manage active sets. At each iteration the duality gap is decreasing, and the process can be stopped earlier on a suboptimal solution. Numerical experiments show that the method is effective on problems with many box constraints and range inequalities.
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