An adaptive stochastic sequential quadratic programming with differentiable exact augmented lagrangians

Exact Nonnull Wavelike Solutions to Gravity with Quadratic Lagrangians

Solutions to gravity with quadratic Lagrangians are found for the simple case where the only nonconstant metric component is the lapse N and the Riemann tensor takes the form R .itj = −kikj , i, j = 1, 2, 3; thus these solutions depend on cross terms in the Riemann tensor and therefore complement the linearized theory where it is the derivatives of the Riemann tensor that matter. The relationsh...

Augmented Lagrangians in semi-infinite programming

We consider the class of semi-infinite programming problems which became in recent years a powerful tool for the mathematical modelling of many real-life problems. In this paper, we study an augmented Lagrangian approach to semi-infinite problems and present necessary and sufficient conditions for the existence of corresponding augmented Lagrange multipliers. Furthermore, we discuss two particu...

Stabilized Sequential Quadratic Programming

Recently, Wright proposed a stabilized sequential quadratic programming algorithm for inequality constrained optimization. Assuming the Mangasarian-Fromovitz constraint qualification and the existence of a strictly positive multiplier (but possibly dependent constraint gradients), he proved a local quadratic convergence result. In this paper, we establish quadratic convergence in cases where bo...

Sequential Quadratic Programming Paul

Sequential Quadratic Programming �

Introduction Since its popularization in the late s Sequential Quadratic Program ming SQP has arguably become the most successful method for solving nonlinearly constrained optimization problems As with most optimization methods SQP is not a single algorithm but rather a conceptual method from which numerous speci c algorithms have evolved Backed by a solid theoretical and computational foundat...