A decomposition approach for stochastic dynamic programming models of reservoir networks

Research output: Contribution to conferenceAbstractpeer-review

Abstract / Description of output

Stochastic dynamic programming is often used to model reservoir control problems. However, in most practical cases, these models are computationally intractable due to the high dimension of the state and action spaces. This paper presents an approach which decomposes the problem into low-dimensional subproblems, each concentrating on one reservoir in the network. The approach works well for certain types of reservoir network under the objective of maximizing expected value. The paper examines how the approach can be adapted for different networks and objectives which take more account of risk.
Original languageEnglish
Publication statusPublished - 2009
Event23rd European Conference on Operational Research: OR Creating Competitive Advantage - Bonn, Germany
Duration: 5 Jul 20098 Jul 2009

Conference

Conference23rd European Conference on Operational Research: OR Creating Competitive Advantage
Country/TerritoryGermany
CityBonn
Period5/07/098/07/09

Keywords / Materials (for Non-textual outputs)

  • Stochastic Models
  • Natural Resources

Fingerprint

Dive into the research topics of 'A decomposition approach for stochastic dynamic programming models of reservoir networks'. Together they form a unique fingerprint.

Cite this