Bound constrained quadratic programming via piecewise quadratic functions
نویسندگان
چکیده
We consider the strictly convex quadratic programming problem with bounded variables. A dual problem is derived using Lagrange duality. The dual problem is the minimization of an unconstrained, piecewise quadratic function. It involves a lower bound of λ1, the smallest eigenvalue of a symmetric, positive definite matrix, and is solved by Newton iteration with line search. The paper describes the algorithm and its implementation including estimation of λ1, how to get a good starting point for the iteration, and upand downdating of Cholesky factorization. Results of extensive testing and comparison with other methods for constrained QP are given.
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ورودعنوان ژورنال:
- Math. Program.
دوره 85 شماره
صفحات -
تاریخ انتشار 1999