Nonconvex Optimization and Its Applications

By: A. J. Kurdilla, Andrew J. Kurdila (Editor), Panos M. Pardalos (Editor)

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Hardcover | 2 December 2005

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284 Pages

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23.39 x 15.6 x 1.75

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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.

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Non-Fiction Reference, Information & Interdisciplinary Subjects Research & Information Information theory Cybernetics & Systems Theory Mathematics Optimisation Linear Programming Applied Mathematics Computing & I.T.Graphical & Digital Media Applications

A multigrid approach to optimal control computations for Navier-Stokes flows	p. 3
Control system radii and robustness under approximation	p. 25
Equilibrium analysis for a network market model	p. 63
Distributed solution of optimal control problems governed by parabolic equations	p. 73
Modeling and implementation of risk-averse preferences in stochastic programs using risk measures	p. 95
Shape optimization of electrodes for piezoelectric actuators	p. 117
Robust static super-replication of barrier options in the Black-Scholes model	p. 135
Numerical techniques in relaxed optimization problems	p. 157
Combining model and test data for optimal determination of percentiles and allowables : CVaR regression approach, part I	p. 179
Combining model and test data for optimal determination of precentiles and allowables : CVaR regression approach, part II	p. 209
Semidefinite programming for sensor network and graph localization	p. 247
Table of Contents provided by Blackwell. All Rights Reserved.

Nonconvex Optimization and Its Applications

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Hardcover

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