Optimality conditions for problems over symmetric cones and a simple augmented Lagrangian method

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Veröffentlicht in:arXiv.org (Aug 31, 2017), p. n/a
1. Verfasser: Lourenço, Bruno F
Weitere Verfasser: Fukuda, Ellen H, Fukushima, Masao
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Cornell University Library, arXiv.org
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022 |a 2331-8422 
035 |a 2076200775 
045 0 |b d20170831 
100 1 |a Lourenço, Bruno F 
245 1 |a Optimality conditions for problems over symmetric cones and a simple augmented Lagrangian method 
260 |b Cornell University Library, arXiv.org  |c Aug 31, 2017 
513 |a Working Paper 
520 3 |a In this work we are interested in nonlinear symmetric cone problems (NSCPs), which contain as special cases nonlinear semidefinite programming, nonlinear second order cone programming and the classical nonlinear programming problems. We explore the possibility of reformulating NSCPs as common nonlinear programs (NLPs), with the aid of squared slack variables. Through this connection, we show how to obtain second order optimality conditions for NSCPs in an easy manner, thus bypassing a number of difficulties associated to the usual variational analytical approach. We then discuss several aspects of this connection. In particular, we show a "sharp" criterion for membership in a symmetric cone that also encodes rank information. Also, we discuss the possibility of importing convergence results from nonlinear programming to NSCPs, which we illustrate by discussing a simple augmented Lagrangian method for nonlinear symmetric cones. We show that, employing the slack variable approach, we can use the results for NLPs to prove convergence results, thus extending a special case (i.e., the case with strict complementarity) of an earlier result by Sun, Sun and Zhang for nonlinear semidefinite programs. 
653 |a Lagrange multiplier 
653 |a Nonlinear programming 
653 |a Cones 
653 |a Cases (containers) 
653 |a Convergence 
653 |a Mathematical analysis 
653 |a Slack variables 
653 |a Semidefinite programming 
653 |a Economic models 
700 1 |a Fukuda, Ellen H 
700 1 |a Fukushima, Masao 
773 0 |t arXiv.org  |g (Aug 31, 2017), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/2076200775/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/1701.05298