A Method for Approximate Solutions to Stochastic Dynamic Programming Problems Using Expectations

J. M. Norman and D. J. White
Additional contact information
J. M. Norman: Arthur D. Little, Inc., Cambridge, Massachusetts
D. J. White: University of Strathclyde, Scotland

Operations Research, 1968, vol. 16, issue 2, 296-306

Abstract: This note describes and illustrates a computational technique to obtain approximate solutions to stochastic dynamic programming problems. The technique is to replace probability distributions by their corresponding expectations, and to use the values of the states in the corresponding deterministic system under its optimal policy to determine an approximate policy in the stochastic system through a single application of Howard's policy improvement operation. Two examples are given.

Date: 1968
References: Add references at CitEc
Citations:

Downloads: (external link)
http://dx.doi.org/10.1287/opre.16.2.296 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:16:y:1968:i:2:p:296-306

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().