Robust Optimization-Directed Design: 81 (Nonconvex by Andrew J. Kurdila,Panos Pardalos,Michael Zabarankin,Panos M. PDF

By Andrew J. Kurdila,Panos Pardalos,Michael Zabarankin,Panos M. Pardalos

powerful design—that is, handling layout uncertainties akin to version uncertainty or parametric uncertainty—is the customarily disagreeable factor the most important in a lot multidisciplinary optimum layout paintings. lately, there was huge, immense useful curiosity in techniques for utilising optimization instruments to the advance of sturdy options and designs in numerous parts, together with aerodynamics, the mixing of sensing (e.g., laser radars, vision-based platforms, and millimeter-wave radars) and regulate, cooperative keep an eye on with poorly modeled uncertainty, cascading disasters in army and civilian purposes, multi-mode seekers/sensor fusion, and knowledge organization difficulties and monitoring platforms. The contributions to this e-book discover those diversified concepts. The expression 'optimization-directed” during this book’s name is intended to indicate that the focal point isn't really agonizing over no matter if optimization concepts determine a real international optimal, yet relatively no matter if those concepts make major layout improvements.

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Robust Optimization-Directed Design: 81 (Nonconvex Optimization and Its Applications (closed)) by Andrew J. Kurdila,Panos Pardalos,Michael Zabarankin,Panos M. Pardalos

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