Approximating linear programming problems which arise in stochastic control

Author

Mendiondo, Marta Susana ; Stockbridge, Richard H.

Author_Institution

Dept. of Stat., Kentucky Univ., Lexington, KY, USA

Volume

2

fYear

1998

fDate

16-18 Dec 1998

Firstpage

2341

Abstract

We study a general approximation scheme for infinite-dimensional linear programming (LP) problems which arise naturally in stochastic control. We prove that the optimal value of the approximating problems converges to the value of the original LP problem. For the controls, we show that if the approximating optimal controls converge, the limiting control is an optimal control for the original LP problem. As an application of this theory, we present numerical approximations to the LP formulation of a long-term average control problem in continuous time

Keywords

Markov processes; approximation theory; continuous time systems; convergence of numerical methods; linear programming; optimal control; probability; state-space methods; stochastic systems; Markov chain; approximation; continuous time systems; convergence; linear programming; optimal control; probability; state space; stochastic control; Constraint optimization; Constraint theory; Cost function; Extraterrestrial measurements; Linear approximation; Linear programming; Optimal control; Statistics; Stochastic processes; Time measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1998. Proceedings of the 37th IEEE Conference on

Conference_Location

Tampa, FL

ISSN

0191-2216

Print_ISBN

0-7803-4394-8

Type

conf

DOI

10.1109/CDC.1998.758694

Filename

758694