Large-Scale PDE-Constrained Optimization

Lorenz T. Biegler

ISBN 10: 3540050450 / ISBN 13: 9783540050452

Published by Springer Berlin Heidelberg Sep 2003, 2003

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -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. 364 pp. Englisch.

Seller Inventory # 9783540050452

Bibliographic Details

• Title: Large-Scale PDE-Constrained Optimization
• Publisher: Springer Berlin Heidelberg Sep 2003
• Publication Date: 2003
• Language: English
• ISBN 10: 3540050450
• ISBN 13: 9783540050452
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 20D millimeters 235 millimeters width by 155 millimeters height by 20 millimeters depth
• Weight: 552 grams

About this title

Synopsis

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.