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Titlebook: Nondifferentiable Optimization and Polynomial Problems; Naum Z. Shor Book 1998 Springer Science+Business Media Dordrecht 1998 Mathematica.

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書目名稱Nondifferentiable Optimization and Polynomial Problems
編輯Naum Z. Shor
視頻videohttp://file.papertrans.cn/668/667242/667242.mp4
叢書名稱Nonconvex Optimization and Its Applications
圖書封面Titlebook: Nondifferentiable Optimization and Polynomial Problems;  Naum Z. Shor Book 1998 Springer Science+Business Media Dordrecht 1998 Mathematica.
描述Polynomial extremal problems (PEP) constitute one of the most important subclasses of nonlinear programming models. Their distinctive feature is that an objective function and constraints can be expressed by polynomial functions in one or several variables. Let :e = {:e 1, ... , :en} be the vector in n-dimensional real linear space Rn; n PO(:e), PI (:e), ... , Pm (:e) are polynomial functions in R with real coefficients. In general, a PEP can be formulated in the following form: (0.1) find r = inf Po(:e) subject to constraints (0.2) Pi (:e) =0, i=l, ... ,m (a constraint in the form of inequality can be written in the form of equality by introducing a new variable: for example, P( x) ~ 0 is equivalent to P(:e) + y2 = 0). Boolean and mixed polynomial problems can be written in usual form by adding for each boolean variable z the equality: Z2 - Z = O. Let a = {al, ... ,a } be integer vector with nonnegative entries {a;}f=l. n Denote by R[a](:e) monomial in n variables of the form: n R[a](:e) = IT :ef‘; ;=1 d(a) = 2:7=1 ai is the total degree of monomial R[a]. Each polynomial in n variables can be written as sum of monomials with nonzero coefficients: P(:e) = L caR[a](:e), aEA{P) IX x
出版日期Book 1998
關(guān)鍵詞Mathematica; algebra; algorithms; calculus; complexity; graph theory; optimization; programming; combinatori
版次1
doihttps://doi.org/10.1007/978-1-4757-6015-6
isbn_softcover978-1-4419-4792-5
isbn_ebook978-1-4757-6015-6Series ISSN 1571-568X
issn_series 1571-568X
copyrightSpringer Science+Business Media Dordrecht 1998
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Decomposition Methods Based on Nonsmooth Optimization,es to the external memory of a computer. Such methods convert the solution of the original problem into the solution of a series of problems of lower dimension (blocks). They are particularly efficient if the structure of each block permits the use of special, fast solution methods, or the structure
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Elements of Convex Analysis, Linear Algebra, and Graph Theory,We shall review a number of fundamental properties of convex sets and functions which will be usefull in the following chapters. This review is based on the latest monographies in convex analysis and optimization, mainly, [Psh 69], [HUL 93], [Roc 70], [Roc 82a], [IT 79], [DV 85].
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978-1-4419-4792-5Springer Science+Business Media Dordrecht 1998
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