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Start Over Topic algorithms Topic mathematical analysis Topic mathematical optimization Topic stochastic convergence Journal international journal of computer mathematics
2 results

1. A new nonmonotone filter Barzilai–Borwein method for solving unconstrained optimization problems.

Author

Arzani, F. and Peyghami, M. Reza

Subjects
*MONOTONE operators, *MATHEMATICAL optimization, *ALGORITHMS, *STOCHASTIC convergence, *NUMERICAL analysis, *MATHEMATICAL analysis
Abstract

In this paper, a finite filter is used in the structure of the Barzilai–Browein (BB) gradient method in order to propose a new modified BB algorithm for solving large-scale unconstrained optimization problems. Our algorithm is equipped with a relaxed nonmonotone line search technique which allows the algorithm to enjoy the nonmonotonicity properties from scratch. Under some suitable conditions, the global convergence property of the new proposed algorithm is established. Numerical results on some test problems in CUTEr library show the efficiency and effectiveness of the new algorithm in practice too. [ABSTRACT FROM PUBLISHER]

Published
2016
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2. Convergence of memory gradient methods.

Author

Shi, Zhen-Jun and Guo, Jinhua

Subjects
*STOCHASTIC convergence, *MATHEMATICAL optimization, *ALGORITHMS, *MATHEMATICAL analysis, *MATHEMATICS
Abstract

In this paper we present a new class of memory gradient methods for unconstrained optimization problems and develop some useful global convergence properties under some mild conditions. In the new algorithms, trust region approach is used to guarantee the global convergence. Numerical results show that some memory gradient methods are stable and efficient in practical computation. In particular, some memory gradient methods can be reduced to the BB method in some special cases. [ABSTRACT FROM AUTHOR]

Published
2008
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