On the Employment of Inexact Restoration for the Minimization of Functions Whose Evaluation Is Subject to Errors

Abstract

© 2017 American Mathematical Society. Inexact Restoration is a well established technique for continuous minimization problems with constraints. Recently, it has been used by Krejić and Martínez for optimization of functions whose evaluation is necessarily inexact and comes from an iterative process. This technique will be generalized in the present paper and it will be applied to stochastic optimization and related problems. New convergence results will be given and numerical results will be presented.