Randomized Algorithms for Semi-Infinite Programming Problems

VB Tadic, SP Meyn, R Tempo

Research output: Chapter in Book/Report/Conference proceedingChapter in a book

Abstract

This paper studies the development of Monte Carlo methods to solve semi-infinite, nonlinear programming problems. An equivalent stochastic optimization problem is proposed, which leads to a class of randomized algorithms based on stochastic approximation. The main results of the paper show that almost sure convergence can be established under relatively mild conditions.
Translated title of the contributionRandomized Algorithms for Semi-Infinite Programming Problems
Original languageEnglish
Title of host publicationProbabilistic and Randomized Methods for Design under Uncertainty
EditorsG. Calafiore, F. Dabene
PublisherSpringer Verlag
Pages243 - 263
Number of pages21
ISBN (Print)184628094X
Publication statusPublished - 2006

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