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Nonlinear symmetric cone programming (NSCP) generalizes important optimization problems such as nonlinear programming, nonlinear semi-definite programming and nonlinear second-order cone programming (NSOCP). In this work, we present two new optimality conditions for NSCP without constraint qualifications, which implies the Karush–Kuhn–Tucker conditions under a condition weaker than Robinson’s constraint qualification. In addition, we show the relationship of both optimality conditions in the context of NSOCP, where we also present an augmented Lagrangian method with global convergence to a KKT point under a condition weaker than Robinson’s constraint qualification.
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; Santos, Daiana O. 4 ; Secchin, Leonardo D. 5 1 University of Campinas, Department of Applied Mathematics, Campinas, Brazil (GRID:grid.411087.b) (ISNI:0000 0001 0723 2494)
2 Kyoto University, Graduate School of Informatics, Kyoto, Japan (GRID:grid.258799.8) (ISNI:0000 0004 0372 2033)
3 University of São Paulo, Department of Applied Mathematics, São Paulo, Brazil (GRID:grid.11899.38) (ISNI:0000 0004 1937 0722)
4 Federal University of São Paulo, Paulista School of Politics, Economics and Business, Osasco, Brazil (GRID:grid.411249.b) (ISNI:0000 0001 0514 7202)
5 Federal University of Espírito Santo, Department of Applied Mathematics, São Mateus, Brazil (GRID:grid.412371.2) (ISNI:0000 0001 2167 4168)