000 | 03668nam a22005175i 4500 | ||
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001 | 978-0-387-28654-9 | ||
003 | DE-He213 | ||
005 | 20161121231024.0 | ||
007 | cr nn 008mamaa | ||
008 | 100301s2006 xxu| s |||| 0|eng d | ||
020 |
_a9780387286549 _9978-0-387-28654-9 |
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024 | 7 |
_a10.1007/0-387-28654-3 _2doi |
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050 | 4 | _aQA402.5-402.6 | |
072 | 7 |
_aPBU _2bicssc |
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_aMAT003000 _2bisacsh |
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_a519.6 _223 |
245 | 1 | 0 |
_aRobust Optimization-Directed Design _h[electronic resource] / _cedited by Andrew J. Kurdila, Panos M. Pardalos, Michael Zabarankin. |
264 | 1 |
_aBoston, MA : _bSpringer US, _c2006. |
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300 |
_aIX, 275 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aNonconvex Optimization and Its Applications, _x1571-568X ; _v81 |
|
505 | 0 | _aA Multigrid Approach to Optimal Control Computations for Navier-Stokes Flows -- Control System Radii and Robustness Under Approximation -- Equilibrium Analysis for a Network Market Model -- Distributed Solution of Optimal Control Problems Governed by Parabolic Equations -- Modeling and Implementation of Risk-Averse Preferences in Stochastic Programs Using Risk Measures -- Shape Optimization of Electrodes for Piezoelectric Actuators -- Robust Static Super-Replication of Barrier Options in the Black-Scholes model -- Numerical Techniques in Relaxed Optimization Problems -- Combining Model and Test Data for Optimal Determination of Percentiles and Allowables: CVaR Regression Approach, Part I -- Combining Model and Test Data for Optimal Determination of Percentiles and Allowables: CVaR Regression Approach, Part II -- Semidefinite Programming for Sensor Network and Graph Localization. | |
520 | _aRobust 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. Audience . | ||
650 | 0 | _aMathematics. | |
650 | 0 | _aApplied mathematics. | |
650 | 0 | _aEngineering mathematics. | |
650 | 0 | _aSystem theory. | |
650 | 0 | _aMathematical optimization. | |
650 | 1 | 4 | _aMathematics. |
650 | 2 | 4 | _aOptimization. |
650 | 2 | 4 | _aApplications of Mathematics. |
650 | 2 | 4 | _aSystems Theory, Control. |
700 | 1 |
_aKurdila, Andrew J. _eeditor. |
|
700 | 1 |
_aPardalos, Panos M. _eeditor. |
|
700 | 1 |
_aZabarankin, Michael. _eeditor. |
|
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9780387282633 |
830 | 0 |
_aNonconvex Optimization and Its Applications, _x1571-568X ; _v81 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/0-387-28654-3 |
912 | _aZDB-2-SMA | ||
950 | _aMathematics and Statistics (Springer-11649) | ||
999 |
_c507410 _d507410 |