In this paper, we propose a new trust region method for unconstrained optimization problems. The new trust region method can automatically adjust the trust region radius of related subproblems at each iteration and has strong global convergence under some mild conditions. We also analyze the global
A hybrid trust region algorithm for unconstrained optimization
β Scribed by Yigui Ou
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 166 KB
- Volume
- 61
- Category
- Article
- ISSN
- 0168-9274
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
## Abstract In this paper, we propose and analyze a new conic trustβregion algorithm for solving the unconstrained optimization problems. A new strategy is proposed to construct the conic model and the relevant conic trustβregion subproblems are solved by an approximate solution method. This approx
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
In this paper, a new trust region algorithm is proposed for solving unconstrained optimization problems. This method can be regarded as a combination of trust region technique, fixed step-length and ODE-based methods. A feature of this proposed method is that at each iteration, only a system of line
## 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