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Indefinitely preconditioned conjugate gradient method for large sparse equality and inequality constrained quadratic problems

✍ Scribed by C. Durazzi; V. Ruggiero


Publisher
John Wiley and Sons
Year
2003
Tongue
English
Weight
144 KB
Volume
10
Category
Article
ISSN
1070-5325

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✦ Synopsis


Abstract

This paper is concerned with the numerical solution of a symmetric indefinite system which is a generalization of the Karush–Kuhn–Tucker system. Following the recent approach of Lukšan and Vlček, we propose to solve this system by a preconditioned conjugate gradient (PCG) algorithm and we devise two indefinite preconditioners with good theoretical properties. In particular, for one of these preconditioners, the finite termination property of the PCG method is stated. The PCG method combined with a parallel version of these preconditioners is used as inner solver within an inexact Interior‐Point (IP) method for the solution of large and sparse quadratic programs. The numerical results obtained by a parallel code implementing the IP method on distributed memory multiprocessor systems enable us to confirm the effectiveness of the proposed approach for problems with special structure in the constraint matrix and in the objective function. Copyright © 2002 John Wiley & Sons, Ltd.


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Indefinitely preconditioned inexact Newt
✍ Ladislav Lukšan; Jan Vlček 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 195 KB 👁 2 views

An inexact Newton algorithm for large sparse equality constrained non-linear programming problems is proposed. This algorithm is based on an indefinitely preconditioned smoothed conjugate gradient method applied to the linear KKT system and uses a simple augmented Lagrangian merit function for Armij