| 期刊全稱 | Bayesian and High-Dimensional Global Optimization | | 影響因子2023 | Anatoly Zhigljavsky,Antanas ?ilinskas | | 視頻video | http://file.papertrans.cn/182/181891/181891.mp4 | | 發(fā)行地址 | Includes examples of the convergence in probability of random search.Examines high-dimensional global optimization problems.Discusses methodological issues in global optimization | | 學(xué)科分類 | SpringerBriefs in Optimization | | 圖書(shū)封面 |  | | 影響因子 | .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 hi | | Pindex | Book 2021 |
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