An inexact linear search and its convergence (Q5891568)
From MaRDI portal
 | This is the item page for this Wikibase entity, intended for internal use and editing purposes. Please use this page instead for the normal view: An inexact linear search and its convergence |
scientific article; zbMATH DE number 6037132
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | An inexact linear search and its convergence |
scientific article; zbMATH DE number 6037132 |
Statements
21 May 2012
0 references
acceptable step-length
0 references
global and super-linear convergence
0 references
inexact one-dimensional descent search
0 references
unconstrained optimization
0 references
0 references
0.91002214
0 references
0.89562917
0 references
0.88794506
0 references
An inexact linear search and its convergence (English)
0 references
The aim of this paper is to present a globally convergent method for solving an unconstrained optimization problem, where the values of the objective function and its gradient are difficult to compute exactly. Based on the Armijo-Goldstein and Wolfe-Powell criterions, a new class of inexact one-dimensional linear search methods is presented, although the traditional method works well. In each iterative process, the method produces its acceptable step-length more reasonable. Compared to the common inexact one-dimensional search, the presented search method can obtain a satisfying descent quantity of the objective function, and has the global convergence as well.
0 references
