In this paper, we present a nonmonotone trust-region method of conic model for unconstrained optimization. The new method combines a new trust-region subproblem of conic model proposed in [Y. Ji, S.J. Qu, Y.J. Wang, H.M. Li, A conic trust-region method for optimization with nonlinear equality and in
A Nonmonotone trust region method with adaptive radius for unconstrained optimization problems
β Scribed by Masoud Ahookhosh; Keyvan Amini
- Publisher
- Elsevier Science
- Year
- 2010
- Tongue
- English
- Weight
- 351 KB
- Volume
- 60
- Category
- Article
- ISSN
- 0898-1221
No coin nor oath required. For personal study only.
β¦ Synopsis
a b s t r a c t
In this paper, we incorporate a nonmonotone technique with the new proposed adaptive trust region radius (Shi and Guo, 2008) [4] in order to propose a new nonmonotone trust region method with an adaptive radius for unconstrained optimization. Both the nonmonotone techniques and adaptive trust region radius strategies can improve the trust region methods in the sense of global convergence. The global convergence to first and second order critical points together with local superlinear and quadratic convergence of the new method under some suitable conditions. Numerical results show that the new method is very efficient and robustness for unconstrained optimization problems.
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