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Titlebook: Modern Numerical Nonlinear Optimization; Neculai Andrei Book 2022 The Editor(s) (if applicable) and The Author(s), under exclusive license

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發(fā)表于 2025-3-21 17:41:59 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Modern Numerical Nonlinear Optimization
編輯Neculai Andrei
視頻videohttp://file.papertrans.cn/638/637308/637308.mp4
概述Nonlinear optimization algorithms for solving large-scale unconstrained and constrained optimization applications.Optimization methods that are currently the most valuable for solving real-life proble
叢書(shū)名稱Springer Optimization and Its Applications
圖書(shū)封面Titlebook: Modern Numerical Nonlinear Optimization;  Neculai Andrei Book 2022 The Editor(s) (if applicable) and The Author(s), under exclusive license
描述.This book includes a thorough theoretical and computational analysis of unconstrained and constrained optimization algorithms and combines and integrates the most recent techniques and advanced computational linear algebra methods. Nonlinear optimization methods and techniques have reached their maturity and an abundance of optimization algorithms are available for which both the convergence properties and the numerical performances are known. This clear, friendly, and rigorous exposition discusses the theory behind the nonlinear optimization algorithms for understanding their properties and their convergence, enabling the reader to prove the convergence of his/her own algorithms. It covers cases and computational performances of the most known modern nonlinear optimization algorithms that solve collections of unconstrained and constrained optimization test problems with different structures, complexities, as well as those with large-scale real applications.. The book is addressed to all those interested in developing and using new advanced techniques for solving large-scale unconstrained or constrained complex optimization problems. Mathematical programming researchers, theoretic
出版日期Book 2022
關(guān)鍵詞unconstrained optimization; stepsize computation; steepest descent method; Newton method; conjugate grad
版次1
doihttps://doi.org/10.1007/978-3-031-08720-2
isbn_softcover978-3-031-08722-6
isbn_ebook978-3-031-08720-2Series ISSN 1931-6828 Series E-ISSN 1931-6836
issn_series 1931-6828
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Modern Numerical Nonlinear Optimization978-3-031-08720-2Series ISSN 1931-6828 Series E-ISSN 1931-6836
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1931-6828 are currently the most valuable for solving real-life proble.This book includes a thorough theoretical and computational analysis of unconstrained and constrained optimization algorithms and combines and integrates the most recent techniques and advanced computational linear algebra methods. Nonline
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Book 2022ates the most recent techniques and advanced computational linear algebra methods. Nonlinear optimization methods and techniques have reached their maturity and an abundance of optimization algorithms are available for which both the convergence properties and the numerical performances are known. T
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