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On the weak second-order optimality condition for nonlinear semidefinite and second-order cone programming

2022/08/05 by Fukuda, Ellen H., Haeser, Gabriel, Mito, Leonardo M. · 2 citations
#90C46 90C30 90C26 90C22 #FOS: Mathematics #Optimization and Control (math.OC)

paper · doi:10.48550/arxiv.2208.03076

Abstract

Second-order necessary optimality conditions for nonlinear conic programming problems that depend on a single Lagrange multiplier are usually built under nondegeneracy and strict complementarity. In this paper we establish a condition of such type for two classes of nonlinear conic problems, namely semidefinite and second-order cone programming, assuming Robinson's constraint qualification and a weak constant rank-type property which are, together, strictly weaker than nondegeneracy. Our approach is done via a penalty-based strategy, which is aimed at providing strong global convergence results for first- and second-order algorithms. Since we are not assuming strict complementarity, the critical cone does not reduce to a subspace, thus, the second-order condition we arrive at is defined in terms of the lineality space of the critical cone. In the case of nonlinear programming, this condition reduces to the standard second-order condition widely used as second-order stationarity measure in the algorithmic practice.

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