Reformulates SDCMPCC via spectral decomposition of complementarity structure and proves augmented Lagrangian accumulation points are W-stationary (or C-stationary under stricter subproblem conditions).
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Approximate directional stationarity is formulated as a necessary optimality condition for nonsmooth constrained problems, with a qualification condition using one sequence to infer directional stationarity.
A solver-agnostic condensing reformulation for linear-quadratic optimization with polyhedral and geometric constraints that preserves augmented-Lagrangian convergence while improving computational speed.
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Augmented Lagrangian methods for nonlinear semidefinite programming with complementarity constraints
Reformulates SDCMPCC via spectral decomposition of complementarity structure and proves augmented Lagrangian accumulation points are W-stationary (or C-stationary under stricter subproblem conditions).
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Approximate directional stationarity and associated qualification conditions
Approximate directional stationarity is formulated as a necessary optimality condition for nonsmooth constrained problems, with a qualification condition using one sequence to infer directional stationarity.
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A condensing approach for linear-quadratic optimization with geometric constraints
A solver-agnostic condensing reformulation for linear-quadratic optimization with polyhedral and geometric constraints that preserves augmented-Lagrangian convergence while improving computational speed.