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Primal Interior Point Method for Minimization of Generalized Minimax Functions
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SYSNO ASEP 0347293 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Primal Interior Point Method for Minimization of Generalized Minimax Functions Author(s) Lukšan, Ladislav (UIVT-O) SAI, RID
Matonoha, Ctirad (UIVT-O) RID, SAI
Vlček, Jan (UIVT-O) SAI, RID, ORCIDSource Title Kybernetika. - : Ústav teorie informace a automatizace AV ČR, v. v. i. - ISSN 0023-5954
Roč. 46, č. 4 (2010), s. 697-721Number of pages 25 s. Language eng - English Country CZ - Czech Republic Keywords unconstrained optimization ; large-scale optimization ; nonsmooth optimization ; generalized minimax optimization ; interior-point methods ; modified Newton methods ; variable metric methods ; global convergence ; computational experiments Subject RIV BA - General Mathematics R&D Projects GA201/09/1957 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10300504 - UIVT-O (2005-2011) UT WOS 000284562000008 EID SCOPUS 79951615907 Annotation In this paper, we propose a primal interior-point method for large sparse generalized minimax optimization. After a short introduction, where the problem is stated, we introduce the basic equations of the Newton method applied to the KKT conditions and propose a primal interior-point method. Next we describe the basic algorithm and give more details concerning its implementation covering numerical differentiation, variable metric updates, and a barrier parameter decrease. Using standard weak assumptions, we prove that this algorithm is globally convergent if a bounded barrier is used. Then, using stronger assumptions, we prove that it is globally convergent also for the logarithmic barrier. Finally, we present results of computational experiments confirming the efficiency of the primal interior point method for special cases of generalized minimax problems. Workplace Institute of Computer Science Contact Tereza Šírová, sirova@cs.cas.cz, Tel.: 266 053 800 Year of Publishing 2011
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