Lecture Notes in Computational Science and Engineering : Lecture Notes in Computational Science and Engineering, 30 - Lorenz T. Biegler

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Lecture Notes in Computational Science and Engineering

By: Lorenz T. Biegler, Omar Ghattas, Matthias Heinkenschloss

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Paperback | 5 September 2003

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364 Pages

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Optimal design, optimal control, and parameter estimation of systems governed by partial differential equations (PDEs) give rise to a class of problems known as PDE-constrained optimization. The size and complexity of the discretized PDEs often pose significant challenges for contemporary optimization methods. With the maturing of technology for PDE simulation, interest has now increased in PDE-based optimization. The chapters in this volume collectively assess the state of the art in PDE-constrained optimization, identify challenges to optimization presented by modern highly parallel PDE simulation codes, and discuss promising algorithmic and software approaches for addressing them. These contributions represent current research of two strong scientific computing communities, in optimization and PDE simulation. This volume merges perspectives in these two different areas and identifies interesting open questions for further research.

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You Can Find This Book In

Non-Fiction Mathematics Calculus & Mathematical Analysis Differential Calculus & Equations Probability & Statistics Engineering & Technology Technology in General Engineering in General Optimisation Linear Programming Computing & I.T.Computer Science

Applied Mathematics Numerical Analysis

Large-Scale PDE-Constrained Optimization: An Introduction	p. 3
Nonlinear Elimination in Aerodynamic Analysis and Design Optimization	p. 17
Optimization of Large-Scale Reacting Flows using MPSalsa and Sequential Quadratic Programming	p. 45
First-Order Approximation and Model Management in Optimization	p. 63
Multifidelity Global Optimization Using DIRECT	p. 80
Inexactness Issues in the Lagrange-Newton-Krylov-Schur Method for PDE-constrained Optimization	p. 93
Solution Adapted Mesh Refinement and Sensitivity Analysis for Parabolic Partial Differential Equation Systems	p. 117
Challenges and Opportunities in Using Automatic Differentiation with Object-Oriented Toolkits for Scientific Computing	p. 133
Piggyback Differentiation and Optimization	p. 148
Assessing the Potential of Interior Methods for Nonlinear Optimization	p. 167
An Interior Point Algorithm for Large Scale Optimization	p. 184
SQP SAND Strategies that Link to Existing Modeling Systems	p. 199
Interior Methods For a Class of Elliptic Variational Inequalities	p. 218
Hierarchical Control of a Linear Diffusion Equation	p. 236
A Sequential Quadratic Programming Method for Nonlinear Model Predictive Control	p. 253
Reduced Order Modelling Approaches to PDE-Constrained Optimization Based on Proper Orthogonal Decomposition	p. 268
Adaptive Simulation, the Adjoint State Method, and Optimization	p. 281
The SIERRA Framework for Developing Advanced Parallel Mechanics Applications	p. 301
rSQP++ : An Object-Oriented Framework for Successive Quadratic Programming	p. 316
Sundance Rapid Prototyping Tool for Parallel PDE Optimization	p. 331
Color Plates	p. 343
Table of Contents provided by Blackwell. All Rights Reserved.

Lecture Notes in Computational Science and Engineering

At a Glance

Paperback

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How to return your order

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