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http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/3296 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/3296 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/3296 archive 351 disk0/00/00/32/55 2016-01-15 01:59:33 2021-08-27 17:13:32 2016-01-15 01:59:33 monograph show 2 Klatte D. AL0853 Kummer B. Walzebok R. Conditions for Optimality and Strong Stability in Nonlinear Programs without assuming Twice Differentiability of Data pub iis_met prog_ado The present paper is concerned with optimization problems in which the data are differentiable functions having a continuous or locally Lipschitzian gradient mapping. Its main purpose is to develop second-order sufficient conditions for a stationary solution to a program with C^{1,1} data to be a strict local minimizer or to be a local minimizer which is even strongly stable with respect to certain perturbations of the data. It turns out that some concept of a set-valued directional derivative of a Lipschitzian mapping is a suitable tool to extend well-known results in the case of programs with twice differentiable data to more general situations. The local minimizers being under consideration have to satisfy the Mangasarian-Fromovitz CQ. An application to iterated local minimization is sketched. 1989-11 published WP-89-089 WP-89-089 10 2041 public working_paper IIASA, Laxenburg, Austria 35 FALSE info:eu-repo/semantics/book