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Displaying similar documents to “New convergence results on an algorithm for norm constrained regularization and related problems”

An accurate active set Newton algorithm for large scale bound constrained optimization

Li Sun, Guoping He, Yongli Wang, Changyin Zhou (2011)

Applications of Mathematics

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A new algorithm for solving large scale bound constrained minimization problems is proposed. The algorithm is based on an accurate identification technique of the active set proposed by Facchinei, Fischer and Kanzow in 1998. A further division of the active set yields the global convergence of the new algorithm. In particular, the convergence rate is superlinear without requiring the strict complementarity assumption. Numerical tests demonstrate the efficiency and performance of the...

Convergence analysis of adaptive trust region methods

Zhen-Jun Shi, Xiang-Sun Zhang, Jie Shen (2007)

RAIRO - Operations Research

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In this paper, we propose a new class of adaptive trust region methods for unconstrained optimization problems and develop some convergence properties. In the new algorithms, we use the current iterative information to define a suitable initial trust region radius at each iteration. The initial trust region radius is more reasonable in the sense that the trust region model and the objective function are more consistent at the current iterate. The global convergence, super-linear and...