Augmented Lagrangian methods for nonlinear semidefinite programming with complementarity constraints

Daiana O. Santos; Carina M. Costa; Evelin H. M. Krulikovski e Marina Geremia

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arXiv · 2606.08424

Augmented Lagrangian methods for nonlinear semidefinite programming with complementarity constraints

Daiana O. Santos·Carina M. Costa·Evelin H. M. Krulikovski e Marina Geremia

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Abstract

We consider nonlinear semidefinite programming problems with complementarity constraints (SDCMPCC), a class of highly degenerate problems where classical optimality conditions typically fail. In this context, weak stationarity conditions have been developed to address their degeneracy. While these notions are well understood, their algorithmic implications remain largely unexplored in semidefinite complementarity settings. We introduce a reformulation based on the spectral decomposition of the complementarity structure, which preserves local solutions and enables a tractable analysis. Within this framework, we analyze an augmented Lagrangian method for SDCMPCC and prove that under a suitable extension of Robinson's condition, every accumulation point of the generated sequence is W-stationary, or C-stationary under a stricter condition for solving the subproblems.

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Daiana O. Santos, Carina M. Costa, Evelin H. M. Krulikovski e Marina Geremia. 2026-06-07. Augmented Lagrangian methods for nonlinear semidefinite programming with complementarity constraints. https://arxiv.org/abs/2606.08424

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