Titlebook: Optimization and Control with Applications; Liqun Qi,Koklay Teo,Xiaoqi Yang Conference proceedings 2005 Springer-Verlag US 2005 algorithm.

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書(shū)目名稱(chēng)Optimization and Control with Applications影響因子(影響力)學(xué)科排名




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書(shū)目名稱(chēng)Optimization and Control with Applications讀者反饋學(xué)科排名

磨碎

The Modified Subgraident Method for Equality Constrained Nonconvex Optimization Problemsteria. We do not use any convexity and differentiability conditions, and show that the sequence of the values of dual function converges to the optimal value. Finally, we demonstrate the presented method on numerical examples.

引導(dǎo)

Inexact Restoration Methods for Nonlinear Programming: Advances and Perspectivesegions are centered not in the current point but in the inexactly restored intermediate one. Global convergence has been proved, based on merit functions of augmented Lagrangian type. In this survey we point out some applications and we relate recent advances in the theory.

gout109

1384-6485 e International Workshop on Optimization and Control with Applications. The book contains 28 papers that are grouped according to four broad topics: duality and optimality conditions, optimization algorithms, optimal control, and variational inequality and equilibrium problems. The specific topics c

鴿子

A Comparison of Two Approaches to Second-Order Subdifferentiability Concepts with Application to Optn directions, using the exposed facets of a convex set of symmetric matrices. This allows us to make a comparison between some optimality conditions. A nonsmooth formulation of a standard smooth mathematical programming problem is used to derive a novel set of sufficient optimality conditions.

范圍廣

An Analysis of the Barzilai and Borwein Gradient Method for Unsymmetric Linear Equationsi and Borwein gradient method for two unsymmetric linear equations with only two variables. Under mild conditions, we prove that the convergence rate of the Barzilai and Borwein gradient method is .-superlinear if the coefficient matrix . has the same eigenvalue; if the eigenvalues of . are different, then the convergence rate is .-superlinear.

SIT

On Minimization of Max-Min Functionsss the application of the cutting angle and discrete gradient methods as well as a special penalization method for solving constrained problems. We report the results of preliminary numerical experiments.

沉積物

bibliophile

An Implementation of Training Dual-nu Support Vector Machinesod for training this class of SVM is described in this chapter. The training is divided into the initialisation process and the optimisation process, with both processes using similar iterative techniques. Implementation issues, such as caching, which reduces the memory usage and redundant kernel calculations are discussed.

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