Robust Optimization-directed Design

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Format: Hardcover
Pub. Date: 2005-12-30
Publisher(s): Springer Verlag
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Summary

Robust design'that is, managing design uncertainties such as model uncertainty or parametric uncertainty'is the often unpleasant issue crucial in much multidisciplinary optimal design work. Recently, there has been enormous practical interest in strategies for applying optimization tools to the development of robust solutions and designs in several areas, including aerodynamics, the integration of sensing (e.g., laser radars, vision-based systems, and millimeter-wave radars) and control, cooperative control with poorly modeled uncertainty, cascading failures in military and civilian applications, multi-mode seekers/sensor fusion, and data association problems and tracking systems. The contributions to this book explore these different strategies. The expression "optimization-directed" in this book's title is meant to suggest that the focus is not agonizing over whether optimization strategies identify a true global optimum, but rather whether these strategies make significant design improvements.

Table of Contents

Preface vii
A Multigrid Approach to Optimal Control Computations for Navier-Stokes Flows
3(22)
E. Aulisa
S. Manservisi
Control System Radii and Robustness Under Approximation
25(38)
John A. Burns
Gunther H. Peichl
Equilibrium Analysis for a Network Market Model
63(10)
Juan F. Escobar
Alejandro Jofre
Distributed Solution of Optimal Control Problems Governed by Parabolic Equations
73(22)
Matthias Heinkenschloss
Michael Herty
Modeling and Implementation of Risk-Averse Preferences in Stochastic Programs Using Risk Measures
95(22)
Pavlo A. Krokhmal
Robert Murphey
Shape Optimization of Electrodes for Piezoelectric Actuators
117(18)
Andrew J. Kurdila
Weijian Wang
Yunfei Feng
Richard J. Prazenica
Robust Static Super-Replication of Barrier Options in the Black-Scholes model
135(22)
Jan H. Maruhn
Ekkehard W. Sachs
Numerical Techniques in Relaxed Optimization Problems
157(22)
Tomas Roubicek
Combining Model and Test Data for Optimal Determination of Percentiles and Allowables: CVaR Regression Approach, Part I
179(30)
Stan Uryasev
A. Alexandre Trindade
Combining Model and Test Data for Optimal Determination of Percentiles and Allowables: CVaR Regression Approach, Part II
209(38)
Stan Uryasev
A. Alexandre Trindade
Semidefinite Programming for Sensor Network and Graph Localization
247
Yinyu Ye

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