Parallel Full Space SQP Lagrange--Newton--Krylov--Schwarz Algorithms for PDE-Constrained Optimization Problems

Optimization problems constrained by nonlinear partial differential equations have been the focus of intense research in scientific computing lately. Current methods for the parallel numerical solution of such problems involve sequential quadratic programming (SQP), with either reduced or full space...

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Veröffentlicht in:	SIAM journal on scientific computing Jg. 27; H. 4; S. 1305 - 1328
Hauptverfasser:	Prudencio, Ernesto E., Byrd, Richard, Cai, Xiao-Chuan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Philadelphia, PA Society for Industrial and Applied Mathematics 01.01.2006
Schlagworte:	Algorithms Boundary conditions Calculus of variations and optimal control Design optimization Exact sciences and technology Lagrange multiplier Mathematical analysis Mathematics Methods Microelectromechanical systems Navier-Stokes equations Numerical analysis Numerical analysis. Scientific computation Numerical linear algebra Numerical methods in mathematical programming, optimization and calculus of variations Partial differential equations, boundary value problems Quadratic programming Reynolds number Sciences and techniques of general use Variables 76D55 Krylov subspace method Computing Partial differential equation Schwarz method Non linear equation 49K20 65F10 Navier Stokes equation Sequential method Numerical solution incom-pressible Navier-Stokes equations 65K10 90C90 93C20 Schwarz preconditioners Newton method 65N55 parallel computing Mathematical programming Control flow 65K05 Reynolds number Initial value problem 90C06 Quadratic programming flow control 65Y05 Constrained optimization Numerical analysis Boundary value problem Scientific computation 76N05 nonlinear partial differential equations constrained optimization inexact Newton method Two-dimensional calculations Parallel computation Domain decomposition Preconditioning 65N22
ISSN:	1064-8275, 1095-7197
Online-Zugang:	Volltext
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