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Robust Optimization-Directed Design
Hoofdkenmerken
Auteur: Andrew J. Kurdila; ‎Panos M. Pardalos; ‎Michael Zabarankin
Titel: Robust Optimization-Directed Design
Uitgever: Springer Nature
ISBN: 9780387286549
ISBN boekversie: 9780387282633
Editie: 1
Prijs: € 107.90
Verschijningsdatum: 04-06-2006
Inhoudelijke kenmerken
Categorie: Applied
Taal: English
Imprint: Springer
Technische kenmerken
Verschijningsvorm: E-book
 

Inhoudsopgave:

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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