primal-dual method
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Primal-Dual-Active-Set-Algorithmus — Der Primal Dual Active Set Algorithmus ist ein Verfahren zur Lösung eines quadratischen Optimierungsproblems über einer konvexen Teilmenge S eines Hilbertraumes V über der Menge Ω. Inhaltsverzeichnis 1 Das Problem 2 Der Algorithmus … Deutsch Wikipedia
Primal-Dual-Active-Set Algorithmus — Der Primal Dual Active Set Algorithmus ist ein Verfahren zur Lösung eines quadratischen Optimierungsproblems über einer konvexen Teilmenge S eines Hilbertraumes V über der Menge Ω. Inhaltsverzeichnis 1 Das Problem 2 Der Algorithmus 3 Anwendungen … Deutsch Wikipedia
Dual problem — In constrained optimization, it is often possible to convert the primal problem (i.e. the original form of the optimization problem) to a dual form, which is termed a dual problem. Usually dual problem refers to the Lagrangian dual problem but… … Wikipedia
Interior point method — Interior point methods (also referred to as barrier methods) are a certain class of algorithms to solve linear and nonlinear convex optimization problems. These algorithms have been inspired by Karmarkar s algorithm, developed by Narendra… … Wikipedia
Mehrotra predictor-corrector method — Mehrotra s predictor corrector method in optimization is an implementation of interior point methods. It was proposed in 1989 by Sanjay Mehrotra. [cite journal|last=Mehrotra|first=S.|title=On the implementation of a primal–dual interior point… … Wikipedia
Mehrotra predictor–corrector method — Mehrotra s predictor–corrector method in optimization is an implementation of interior point methods. It was proposed in 1989 by Sanjay Mehrotra.[1] The method is based on the fact that at each iteration of an interior point algorithm it is… … Wikipedia
Decomposition method (constraint satisfaction) — In constraint satisfaction, a decomposition method translates a constraint satisfaction problem into another constraint satisfaction problem that is binary and acyclic. Decomposition methods work by grouping variables into sets, and solving a… … Wikipedia
Constraint satisfaction dual problem — The dual problem is a reformulation of a constraint satisfaction problem expressing each constraint of the original problem as a variable. Dual problems only contain binary constraints, and are therefore solvable by algorithms tailored for such… … Wikipedia
Subgradient method — Subgradient methods are algorithms for solving convex optimization problems. Originally developed by Naum Z. Shor and others in the 1960s and 1970s, subgradient methods can be used with a non differentiable objective function. When the objective… … Wikipedia
Optimisation linéaire — En optimisation, qui est une branche des mathématiques, un problème d optimisation linéaire est un problème d optimisation dans lequel on minimise une fonction linéaire sur un polyèdre convexe. La fonction coût et les contraintes peuvent donc… … Wikipédia en Français
K-approximation of k-hitting set — In computer science, k approximation of k hitting set is an approximation algorithm for weighted hitting set. The input is a collection S of subsets of some universe T and a mapping W from S to non negative numbers called the weights of the… … Wikipedia
