Solving Reduced KKT Systems in Barrier Methods for Linear and Quadratic Programming | Zendy

Philip E. Gill | Zendy; Walter Murray | Zendy; Dulce B. Ponceleón | Zendy; Michael A. Saunders | Zendy

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Solving Reduced KKT Systems in Barrier Methods for Linear and Quadratic Programming

Author(s) -

Philip E. Gill,

Walter Murray,

Dulce B. Ponceleón,

Michael A. Saunders

Publication year - 1991

Publication title -

citeseer x (the pennsylvania state university)

Language(s) - English

Resource type - Reports

DOI - 10.21236/ada239191

Subject(s) - karush–kuhn–tucker conditions , quadratic programming , quadratic equation , mathematical optimization , computer science , mathematics , geometry

: In barrier methods for constrained optimization, the main work lies in solving large linear systems Kp = r, where K is symmetric and indefinite. We have implemented reduced KKT systems in a primal-dual algorithm for linear programming, based on the sparse indefinite solver MA27 from the Harwell Subroutine Library. Some features of the algorithm are presented, along with results on the netlib LP test set.

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