J. A. Gómez, M. Romero
Global convergence of multidirectional algorithmus for unconstrained optimization in normed spaces
Preprint series: Institut für Mathematik, Humboldt-Universität zu Berlin (ISSN 0863-0976)

MSC:

49M10 Methods of steepest descent type

49M37 Nonlinear programming, See also {90C30}

65K10 Optimization and variational techniques, See also {49Mxx,

Abstract: Global convergence theorems for a class of descent methods for unconstrained optimization problems in normed spaces, using multidirectional search, are proved. Exact and inexact search are considered and the results allow to define a globally convergent algoritm for an unconstrained optimal control problem which operates, at each step, on discrete approximations of the original continuous problem.