Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
481993 | European Journal of Operational Research | 2008 | 17 Pages |
Abstract
This paper describes a new algorithm for the solution of nonconvex unconstrained optimization problems, with the property of converging to points satisfying second-order necessary optimality conditions. The algorithm is based on a procedure which, from two descent directions, a Newton-type direction and a direction of negative curvature, selects in each iteration the linesearch model best adapted to the properties of these directions. The paper also presents results of numerical experiments that illustrate its practical efficiency.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Alberto Olivares, Javier M. Moguerza, Francisco J. Prieto,