On Stability of Multistage Stochastic Decision Problems

Alexander Mänz () and Silvia Voge1 ()
Additional contact information
Alexander Mänz: ASPECTA Lebensversicherung AG
Silvia Voge1: Technische Universitäet Ilmenau

A chapter in Recent Advances in Optimization, 2006, pp 103-118 from Springer

Abstract: Summary The paper considers a general multistage stochastic decision problem which contains Markovian decision processes and multistage stochastic programming problems as special cases. The objective functions, the constraint sets and the probability measures are approximated. Making use of the Bellman Principle, (semi) convergence statements for the optimal value functions and the optimal decisions at each stage are derived. The considerations rely on stability assertions for parametric programming problems which are extended and adapted to the multistage case. Furthermore, new sufficient conditions for the convergence of objective functions which are integrals with respect to decision-dependent probability measures are presented. The paper generalizes results by Langen(1981) with respect to the convergence notions, the integrability conditions and the continuity assumptions.

Keywords: Probability Measure; Stochastic Programming; Markovian Decision Process; Borel Subset; Stochastic Programming Problem (search for similar items in EconPapers)
Date: 2006
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:lnechp:978-3-540-28258-7_7

Ordering information: This item can be ordered from
http://www.springer.com/9783540282587

DOI: 10.1007/3-540-28258-0_7

Access Statistics for this chapter

More chapters in Lecture Notes in Economics and Mathematical Systems from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().