Titlebook: Quasidifferential Calculus; V. F. Demyanov,L. C. W. Dixon Book 1986Latest edition Springer-Verlag Berlin Heidelberg 1986 differential calc

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書目名稱Quasidifferential Calculus影響因子(影響力)




書目名稱Quasidifferential Calculus影響因子(影響力)學(xué)科排名




書目名稱Quasidifferential Calculus網(wǎng)絡(luò)公開度




書目名稱Quasidifferential Calculus網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Quasidifferential Calculus被引頻次




書目名稱Quasidifferential Calculus被引頻次學(xué)科排名




書目名稱Quasidifferential Calculus年度引用




書目名稱Quasidifferential Calculus年度引用學(xué)科排名




書目名稱Quasidifferential Calculus讀者反饋




書目名稱Quasidifferential Calculus讀者反饋學(xué)科排名

類型

Quasidifferentiable functions: Necessary conditions and descent directions, It is important that the optimality conditions should be expressed in a form which yields some information concerning search directions if the point under examination does not satisfy the necessary conditions. It is shown that most of the conditions discussed here provide such information.

褲子

膽小鬼

A directional implicit function theorem for quasidifferentiable functions,urciau, J. Warga). In this paper, we consider the case of quasidifferentiable functions. It is shown that to obtain nontrivial results it is necessary to study a directional implicit function problem (it turns out that in some directions there are several functions, while in others there are none).

污點(diǎn)

Jacket

DUST

Resistance

Quasidifferentiable functions: Necessary conditions and descent directions,erentials of the functions involved (i.e., the function to be optimized and a function describing the set over which optimization is to be performed). It is important that the optimality conditions should be expressed in a form which yields some information concerning search directions if the point

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Quasidifferential calculus and first-order optimality conditions in nonsmooth optimization,ly homogeneous functions representable as the sum of sublinear and superlinear functions or, equivalently, as the difference of two sublinear functions (d.s.l. functions). The resulting optimality conditions are expressed in the form of set inclusions. The idea of such approximations is exploited th

violate

On minimizing the sum of a convex function and a concave function,ex function and a concave function. It is shown that in an .-dimensional space this problem is equivalent to the problem of minimizing a concave function on a convex set. A successive approximations method is suggested; this makes use of some of the principles of ∈-steepest-descent-type approaches.