Name
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-Ribiere-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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.cam.2009.08.001 | J. Computational Applied Mathematics |
Keywords | Field | DocType |
important property,search direction,modified conjugate gradient method,global convergence,following property,steepest descent direction,zoutendijk condition,sufficient descent property,unconstrained optimization,wolfe-powell line search technique,line search,steepest descent,trust region,conjugate gradient method,convergence rate,satisfiability | Conjugate gradient method,Gradient method,Trust region,Gradient descent,Mathematical optimization,Algorithm,Descent direction,Line search,Nonlinear conjugate gradient method,Rate of convergence,Mathematics | Journal |
Volume | Issue | ISSN |
233 | 2 | 0377-0427 |
Citations | PageRank | References |
18 | 0.77 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gonglin Yuan | 1 | 215 | 13.71 |
| Xiwen Lu | 2 | 182 | 21.03 |
| Zengxin Wei | 3 | 373 | 28.04 |