caa a22 4500 475769562 CHVBK 20180406123616.0 cr unu---uuuuu 170329e20000601xx s 000 0 eng 10.1007/PL00011370 doi (NATIONALLICENCE)springer-10.1007/PL00011370 Forsgren Anders Optimization and Systems Theory, Department of Mathematics, Royal Institute of Technology, SE-100 44 Stockholm, Sweden, e-mail: anders.forsgren@math.kth.se, SE aut Optimality conditions for nonconvex semidefinite programming [Elektronische Daten] [Anders Forsgren] Abstract. : This paper concerns nonlinear semidefinite programming problems for which no convexity assumptions can be made. We derive first- and second-order optimality conditions analogous to those for nonlinear programming. Using techniques similar to those used in nonlinear programming, we extend existing theory to cover situations where the constraint matrix is structurally sparse. The discussion covers the case when strict complementarity does not hold. The regularity conditions used are consistent with those of nonlinear programming in the sense that the conventional optimality conditions for nonlinear programming are obtained when the constraint matrix is diagonal. Springer-Verlag Berlin Heidelberg, 2000 Key words: semidefinite programming - constrained minimization - optimality conditions - interior methods nationallicence https://doi.org/10.1007/PL00011370 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/PL00011370 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Forsgren Anders Optimization and Systems Theory, Department of Mathematics, Royal Institute of Technology, SE-100 44 Stockholm, Sweden, e-mail: anders.forsgren@math.kth.se, SE aut Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer