| 期刊全稱 | Approximation Methods for Polynomial Optimization | | 期刊簡(jiǎn)稱 | Models, Algorithms, | | 影響因子2023 | Zhening Li,Simai He,Shuzhong Zhang | | 視頻video | http://file.papertrans.cn/161/160388/160388.mp4 | | 發(fā)行地址 | Discuss some important subclasses of polynomial optimization models arising from various applications.Focuses on approximations algorithms with guaranteed worst case performance analysis.Presents a cl | | 學(xué)科分類 | SpringerBriefs in Optimization | | 圖書封面 |  | | 影響因子 | .Polynomial optimization have been a hot research topic for the past few years and its applications range from Operations Research, biomedical engineering, investment science, to quantum mechanics, linear algebra, and signal processing, among many others. In this brief the authors discuss some important subclasses of polynomial optimization models arising from various applications, with a focus on approximations algorithms with guaranteed worst case performance analysis. The brief presents a clear view of the basic ideas underlying the design of such algorithms and the benefits are highlighted by illustrative examples showing the possible applications..?.This timely treatise will appeal to researchers and graduate students in the fields of optimization, computational mathematics, Operations Research, industrial engineering, and computer science.. | | Pindex | Book 2012 |
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