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Derivative-free optimization, a class of nonlinear optimization techniques useful when derivatives are unavailable or unreliable, have applications in fields including computer circuit design, engineering design, finance, operations research, and medicine. In this volume for the Society for Industrial and Applied Mathematics and the Mathematical Programming Society, Conn (IBM Thomas J. Watson Research Center, Yorktown Heights, New York), and colleagues at the Center and the U. of Coimbra, Portugal, present a unified view of recent developments in derivative-free optimization. After introducing core concepts, they present examples of problem frameworks and algorithms. Other topics discussed include surrogate modeling and optimization extensions. The text includes chapter exercises and a list of software packages developed for derivative-free optimization. Annotation c2009 Book News, Inc., Portland, OR (booknews.com)
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