Title :
Randomized algorithms for semi-infinite programming problems
Author :
Tadic, Vladislav B. ; Meyn, Sean P. ; Tempo, Roberto
Author_Institution :
Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield S1 3JD, UK
Abstract :
In this paper, we explore the possibility of applying Monte Carlo methods (i.e., randomization) to semi-infinite programming problems. Equivalent stochastic optimization problems are derived for a general class of semi-infinite programming problems. For the equivalent stochastic optimization problems, algorithms based on stochastic approximation and Monte Carlo sampling methods are proposed. The asymptotic behavior of the proposed algorithms is analyzed and sufficient conditions for their almost sure convergence are obtained.
Keywords :
Algorithm design and analysis; Approximation algorithms; Approximation methods; Monte Carlo methods; Optimization; Programming; Stochastic processes; Monte Carlo methods; Randomized algorithms; semi-infinite programming; stochastic approximation; stochastic optimization;
Conference_Titel :
European Control Conference (ECC), 2003
Conference_Location :
Cambridge, UK
Print_ISBN :
978-3-9524173-7-9
