Robust Optimization-Directed Design (Nonconvex Optimization and Its Applications, 81)

Kurdila, Andrew J. [Editor]; Pardalos, Panos M. [Editor]; Zabarankin, Michael [Editor];

ISBN 10: 0387282637 / ISBN 13: 9780387282633

Verlag: Springer, 2006

Beschreibung

Springer Verlag; Berlin, 2006. Hardcover. A Near Fine, binding firm, trace handling/scuff marks to boards, mild edge/corner wear, small dent bottom spine edge, without Dust wrapper. A nice, clean and unmarked copy. 8vo[octavo or approx. 6 x 9 inches], 275pp., references. We pack securely and ship daily with delivery confirmation on every book. The picture on the listing page is of the actual book for sale. Additional Scan(s) are available for any item, please inquire.Please note: Oversized books/sets MAY require additional postage then what is quoted for 2.2lb book.

Bestandsnummer des Verkäufers SKU1037137

Bibliografische Details

• Titel: Robust Optimization-Directed Design (Nonconvex Optimization and Its Applications, 81)
• Verlag: Springer
• Erscheinungsjahr: 2006
• Sprache: Englisch
• ISBN-10: 0387282637
• ISBN-13: 9780387282633
• Einband: hardcover
• Zustand: As New
• Verkäuferkataloge:
  • Math Text Books

Über diesen Titel

Inhaltsangabe

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.

Von der hinteren Coverseite

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.

Audience