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Bayesian and High-Dimensional Global Optimization (English, Bulgarian, Paperback, 1st ed. 2021)
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Bayesian and High-Dimensional Global Optimization (English, Bulgarian, Paperback, 1st ed. 2021)
Series: SpringerBriefs in Optimization
Expected to ship within 10 - 15 working days
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Accessible to a variety of readers, this book is of interest to
specialists, graduate students and researchers in mathematics,
optimization, computer science, operations research, management
science, engineering and other applied areas interested in solving
optimization problems. Basic principles, potential and boundaries
of applicability of stochastic global optimization techniques are
examined in this book. A variety of issues that face specialists in
global optimization are explored, such as multidimensional spaces
which are frequently ignored by researchers. The importance of
precise interpretation of the mathematical results in assessments
of optimization methods is demonstrated through examples of
convergence in probability of random search. Methodological issues
concerning construction and applicability of stochastic global
optimization methods are discussed, including the one-step optimal
average improvement method based on a statistical model of the
objective function. A significant portion of this book is devoted
to an analysis of high-dimensional global optimization problems and
the so-called 'curse of dimensionality'. An examination of the
three different classes of high-dimensional optimization problems,
the geometry of high-dimensional balls and cubes, very slow
convergence of global random search algorithms in large-dimensional
problems , and poor uniformity of the uniformly distributed
sequences of points are included in this book.
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