A QP Free Feasible Method

A QP Free Feasible Method

Year:    2004

Author:    Dingguo Pu, Yan Zhou, Haiyan Zhang

Journal of Computational Mathematics, Vol. 22 (2004), Iss. 5 : pp. 651–660

Abstract

In [12], a QP free feasible method was proposed for the minimization of a smooth function subject to smooth inequality constraints. This method is based on the solutions of linear systems of equations, the reformulation of the KKT optimality conditions by using the Fischer-Burmeister NCP function. This method ensures the feasibility of all iterations. In this paper, we modify the method in [12] slightly to obtain the local convergence under some weaker conditions. In particular, this method is implementable and globally convergent without assuming the linear independence of the gradients of active constrained functions and the uniformly positive definiteness of the submatrix obtained by the Newton or Quasi Newton methods. We also prove that the method has superlinear convergence rate under some mild conditions. Some preliminary numerical results indicate that this new QP free feasible method is quite promising.  

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2004-JCM-8864

Journal of Computational Mathematics, Vol. 22 (2004), Iss. 5 : pp. 651–660

Published online:    2004-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    10

Keywords:    Constrained optimization KKT point Multiplier Nonlinear complementarity Convergence.

Author Details

Dingguo Pu

Yan Zhou

Haiyan Zhang