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Titlebook: Elementary Convexity with Optimization; Vivek S. Borkar,K. S. Mallikarjuna Rao Textbook 2023 Hindustan Book Agency 2023 optimization.condi

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樓主
發(fā)表于 2025-3-21 19:18:34 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Elementary Convexity with Optimization
編輯Vivek S. Borkar,K. S. Mallikarjuna Rao
視頻videohttp://file.papertrans.cn/308/307369/307369.mp4
概述Develops the concepts of fundamental convex analysis and optimization.Emphasizes on the geometric intuition of convex analysis and optimization.Uses elementary alternative proofs of many results and a
叢書名稱Texts and Readings in Mathematics
圖書封面Titlebook: Elementary Convexity with Optimization;  Vivek S. Borkar,K. S. Mallikarjuna Rao Textbook 2023 Hindustan Book Agency 2023 optimization.condi
描述.This book develops the concepts of fundamental convex analysis and optimization by using advanced calculus and real analysis. Brief accounts of advanced calculus and real analysis are included within the book. The emphasis is on building a geometric intuition for the subject, which is aided further by supporting figures. Two distinguishing features of this book are the use of elementary alternative proofs of many results and an eclectic collection of useful concepts from optimization and convexity often needed by researchers in optimization, game theory, control theory, and mathematical economics. A full chapter on optimization algorithms gives an overview of the field, touching upon many current themes. The book is useful to advanced undergraduate and graduate students as well as researchers in the fields mentioned above and in various engineering disciplines..
出版日期Textbook 2023
關(guān)鍵詞optimization; conditions for optimality; algorithms; convexity; existence of optima; duality
版次1
doihttps://doi.org/10.1007/978-981-99-1652-8
isbn_softcover978-981-99-1651-1
isbn_ebook978-981-99-1652-8Series ISSN 2366-8717 Series E-ISSN 2366-8725
issn_series 2366-8717
copyrightHindustan Book Agency 2023
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沙發(fā)
發(fā)表于 2025-3-21 23:58:01 | 只看該作者
G. Darai,M. Handermann,E. Hinz,H.-G. SonntagIn this chapter we give an overview of a variety of facts concerning optimality of a point relative to a neighborhood of it, in terms of ‘local’ objects such as derivatives. We first introduce the different notions of derivatives and beginning with some familiar conditions for optimality from calculus, build up various generalizations thereof.
板凳
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地板
發(fā)表于 2025-3-22 04:43:56 | 只看該作者
https://doi.org/10.1007/978-3-642-15126-2This chapter is devoted to convex functions, the rock star of optimization theory. In this section, we recall their key properties that matter for convex optimization.
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發(fā)表于 2025-3-22 10:16:12 | 只看該作者
https://doi.org/10.1007/978-3-540-72550-3Convex optimization or convex programming refers to the problem of minimizing convex functions over convex sets. Observe that we have been careful to say only minimization. Maximization of convex functions is a different kettle of fish; altogether, these problems can be extremely hard.
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發(fā)表于 2025-3-22 16:54:19 | 只看該作者
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發(fā)表于 2025-3-22 23:08:51 | 只看該作者
,Continuity and?Existence of?Optima,Optimization theory in finite dimensional spaces may be viewed as ‘a(chǎn)pplied real analysis’, since it depends on the analytic tools of the latter discipline for most of its foundations.
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發(fā)表于 2025-3-23 04:29:17 | 只看該作者
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發(fā)表于 2025-3-23 06:53:27 | 只看該作者
Convex Sets,Recall that a convex set . is a set such that any line segment joining two distinct points in . lies entirely in ., i.e., . implies ..
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