A finite algorithm for global quadratic minimization. (English) Zbl 0692.90076
The paper presents an algorithm that in a finite number of iterations finds an absolute minimizer for the standard quadratic programming problem with no assumptions on convexity properties of the cost function. It is based on the sequential solution of auxiliary linear complementarity problems by an algorithm recently developed by the author. Some results of computational experiments with test problems of dimensions up to 500 are given.
Reviewer: V.S.Izhutkin
MSC:
90C20 | Quadratic programming |
65K05 | Numerical mathematical programming methods |
90C33 | Complementarity and equilibrium problems and variational inequalities (finite dimensions) (aspects of mathematical programming) |