A trust-region method with a conic model for unconstrained optimization
β Scribed by Shao-Jian Qu; Su-Da Jiang
- Publisher
- John Wiley and Sons
- Year
- 2008
- Tongue
- English
- Weight
- 216 KB
- Volume
- 31
- Category
- Article
- ISSN
- 0170-4214
- DOI
- 10.1002/mma.997
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β¦ Synopsis
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 approximate solution method is not only easy to implement but also preserves the strong convergence properties of the exact solution methods. Under reasonable conditions, the locally linear and superlinear convergence of the proposed algorithm is established. The numerical experiments show that this algorithm is both feasible and efficient. Copyright Β© 2008 John Wiley & Sons, Ltd.
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