In several applications, semideenite programs with nonlinear equality constraints arise. We give two such examples to emphasize the importance of this class of problems. We then propose a new solution method that also applies to smooth nonconvex programs. The method combines ideas of a predictor corrector interior-point method, of the SQP method, and of trust region methods. In particular, we b...

This paper presents an extensible framework for optimizing analog lter designs for multiple behavioral and implementation properties. We demonstrate the framework using the behavioral properties of magnitude response, phase response, and peak overshoot, and the implementation property of quality factors. We represent the analog lter in terms of its poles and zeroes. We match the constrained non...

This paper studies Newton-type methods for minimization of partly smooth convex functions. Sequential Newton methods are provided using local parameterizations obtained from U -Lagrangian theory and from Riemannian geometry. The Hessian based on the U -Lagrangian depends on the selection of a dual parameter g; by revealing the connection to Riemannian geometry, a natural choice of g emerges for...

This paper studies Newton-type methods for minimization of partly smooth convex functions. Sequential Newton methods are provided using local parameterizations obtained from U-Lagrangian theory and from Riemannian geometry. The Hessian based on the ULagrangian depends on the selection of a dual parameter g; by revealing the connection to Riemannian geometry, a natural choice of g emerges for wh...

We consider solving nonlinear optimization problems with a stochastic objective and deterministic equality constraints. assume for the that its evaluation, gradient, Hessian are inaccessible, while one can compute their estimates by, example, subsampling. propose algorithm based on sequential quadratic programming (SQP) uses differentiable exact augmented Lagrangian as merit function. To motiva...

This paper presents an approach to the design of optimal control strategy for plug-in hybrid electric vehicles (PHEVs) incorporating Internet Vehicles (IoVs). The is designed and implemented by employing a mobile edge computing (MEC) based framework IoVs. thresholds in can be instantaneously optimized chaotic particle swarm optimization with sequential quadratic programming (CPSO-SQP) units (ME...

• The proposed method utilizes the linear conservation law of regularization continuation such that it does not need to compute correction step for preserving feasibility other than previous methods and quasi-Newton updating formulas. replaces pre-conditioner with inverse two-sided projection Lagrangian Hessian as pre- conditioner improve its robustness in ill-posed phase. This paper considers ...