Andreas Wäechter
YOU?
Author Swipe
View article: A Quadratically Convergent Sequential Programming Method for Second-Order Cone Programs Capable of Warm Starts
A Quadratically Convergent Sequential Programming Method for Second-Order Cone Programs Capable of Warm Starts Open
We propose a new method for linear second-order cone programs. It is based on the sequential quadratic programming framework for nonlinear programming. In contrast to interior point methods, it can capitalize on the warm-start capabilities…
View article: DC Optimal Power Flow With Joint Chance Constraints
DC Optimal Power Flow With Joint Chance Constraints Open
Managing uncertainty and variability in power injections has become a major concern for power system operators due to the increasing levels of fluctuating renewable energy connected to the grid. This work addresses this uncertainty via a j…
View article: A Two-Stage Decomposition Approach for AC Optimal Power Flow
A Two-Stage Decomposition Approach for AC Optimal Power Flow Open
The alternating current optimal power flow (AC-OPF) problem is critical to power system operations and planning, but it is generally hard to solve due to its nonconvex and large-scale nature. This paper proposes a scalable decomposition ap…
View article: A Limited-Memory Quasi-Newton Algorithm for Bound-Constrained Nonsmooth Optimization
A Limited-Memory Quasi-Newton Algorithm for Bound-Constrained Nonsmooth Optimization Open
We consider the problem of minimizing a continuous function that may be nonsmooth and nonconvex, subject to bound constraints. We propose an algorithm that uses the L-BFGS quasi-Newton approximation of the problem's curvature together with…
View article: A Second-Order Method for Convex $\ell_1$-Regularized Optimization with Active Set Prediction
A Second-Order Method for Convex $\ell_1$-Regularized Optimization with Active Set Prediction Open
We describe an active-set method for the minimization of an objective function $ϕ$ that is the sum of a smooth convex function and an $\ell_1$-regularization term. A distinctive feature of the method is the way in which active-set identifi…
View article: A Second-Order Method for Convex $\\ell_1$-Regularized Optimization with\n Active Set Prediction
A Second-Order Method for Convex $\\ell_1$-Regularized Optimization with\n Active Set Prediction Open
We describe an active-set method for the minimization of an objective\nfunction $\\phi$ that is the sum of a smooth convex function and an\n$\\ell_1$-regularization term. A distinctive feature of the method is the way in\nwhich active-set …