Trust Region Newton With Dogleg Method
| dc.contributor.advisor | Guta, Berhanu (PhD) | |
| dc.contributor.author | Yeshitla, Abaye | |
| dc.date.accessioned | 2019-05-22T08:13:55Z | |
| dc.date.accessioned | 2023-11-09T11:25:55Z | |
| dc.date.available | 2019-05-22T08:13:55Z | |
| dc.date.available | 2023-11-09T11:25:55Z | |
| dc.date.issued | 2018-05-02 | |
| dc.description.abstract | In this project, we propose a trust region dogleg method algorithms to solve a trust region subproblems arising form unconstrained optimization. The method can deal with by constricting a dogleg paths. The case when the Hessian B of quadratic models is positive de nite. The philosophy and fundamental ideas of trust region algorithms are discussed and proved that the method is globally convergent and has a supper linear convergence rate. And then the nal algorithm is programmed in MATLAB and implemented by taking appropriate test problem. | en_US |
| dc.identifier.uri | http://10.90.10.223:4000/handle/123456789/18286 | |
| dc.language.iso | en | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Trust Region | en_US |
| dc.subject | Dogleg Path | en_US |
| dc.subject | Dogleg Method | en_US |
| dc.subject | Convergence | en_US |
| dc.title | Trust Region Newton With Dogleg Method | en_US |
| dc.type | Thesis | en_US |