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Inner solvers for interior point methods for large scale nonlinear programming

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Abstract

This paper deals with the solution of nonlinear programming problems arising from elliptic control problems by an interior point scheme. At each step of the scheme, we have to solve a large scale symmetric and indefinite system; inner iterative solvers, with an adaptive stopping rule, can be used in order to avoid unnecessary inner iterations, especially when the current outer iterate is far from the solution.

In this work, we analyse the method of multipliers and the preconditioned conjugate gradient method as inner solvers for interior point schemes. We discuss the convergence of the whole approach, the implementation details and report the results of numerical experimentation on a set of large scale test problems arising from the discretization of elliptic control problems. A comparison with other interior point codes is also reported.

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Correspondence to Emanuele Galligani.

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This research was supported by the Italian Ministry for Education, University and Research (MIUR) projects: FIRB Project: “Parallel Nonlinear Numerical Optimization PN 2 O” (grant n. RBAU01JYPN, http://dm.unife.it/pn2o/) and COFIN/PRIN04 Project “Numerical Methods and Mathematical Software for Applications” (grant n. 2004012559, http://www.math.unifi.it/~brugnano/Cofin2004/).

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Bonettini, S., Galligani, E. & Ruggiero, V. Inner solvers for interior point methods for large scale nonlinear programming. Comput Optim Appl 37, 1–34 (2007). https://doi.org/10.1007/s10589-007-9012-5

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