Non-parametric approximation of non-anticipativity constraints in scenario-based multistage stochastic programming

Title:

Non-parametric approximation of non-anticipativity constraints in scenario-based multistage stochastic programming

Creator:

Roy, Jean-Sébastien and Lenoir, Arnaud

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:864709cb-e4da-4bed-a4c4-efcfbd151f43
uuid:864709cb-e4da-4bed-a4c4-efcfbd151f43

Subject:

multistage stochasti programming, scenarios, and discrete approximation

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

We propose two methods to solve multistage stochastic programs when only a (large) finite set of scenarios is available. The usual scenario tree construction to represent non-anticipativity constraints is replaced by alternative discretization schemes coming from non-parametric estimation ideas. In the first method, a penalty term is added to the objective so as to enforce the closeness between decision variables and the Nadaraya-Watson estimation of their conditional expectation. A numerical application of this approach on an hydro-power plant management problem is developed. The second method exploits the interpretation of kernel estimators as a sum of basis functions.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Coverage:

[171]-184

Source:

Kybernetika | 2008 Volume:44 | Number:2

Harvested from:

CDK

Metadata only:

false