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A conjugate gradient method with descent direction for unconstrained optimization
- Source :
-
Journal of Computational & Applied Mathematics . Nov2009, Vol. 233 Issue 2, p519-530. 12p. - Publication Year :
- 2009
-
Abstract
- Abstract: A modified conjugate gradient method is presented for solving unconstrained optimization problems, which possesses the following properties: (i) The sufficient descent property is satisfied without any line search; (ii) The search direction will be in a trust region automatically; (iii) The Zoutendijk condition holds for the Wolfe–Powell line search technique; (iv) This method inherits an important property of the well-known Polak–Ribière–Polyak (PRP) method: the tendency to turn towards the steepest descent direction if a small step is generated away from the solution, preventing a sequence of tiny steps from happening. The global convergence and the linearly convergent rate of the given method are established. Numerical results show that this method is interesting. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 03770427
- Volume :
- 233
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Journal of Computational & Applied Mathematics
- Publication Type :
- Academic Journal
- Accession number :
- 44118449
- Full Text :
- https://doi.org/10.1016/j.cam.2009.08.001