Minimizing risk models in stochastic shortest path problems

Yoshio Ohtsubo

Mathematical Methods of Operations Research, 2003, vol. 57, issue 1, 79-88

Abstract: We consider a minimizing risk model in a stochastic shortest path problem in which for each node of a graph we select a probability distribution over the set of successor nodes so as to reach a given target node with minimum threshold probability. We formulate such a problem as undiscounted finite Markov decision processes. We show that an optimal value function is a unique solution to an optimality equation and find an optimal stationary policy. A value iteration method is also given. Copyright Springer-Verlag Berlin Heidelberg 2003

Keywords: Key words: shortest path problem; minimizing risk model; Markov decision process (search for similar items in EconPapers)
Date: 2003
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://hdl.handle.net/10.1007/s001860200246 (text/html)
Access to full text is restricted to subscribers.

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:mathme:v:57:y:2003:i:1:p:79-88

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/00186

DOI: 10.1007/s001860200246

Access Statistics for this article

Mathematical Methods of Operations Research is currently edited by Oliver Stein

More articles in Mathematical Methods of Operations Research from Springer, Gesellschaft für Operations Research (GOR), Nederlands Genootschap voor Besliskunde (NGB)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().