Rougé, C. and Tilmant, A. (2016) Using stochastic dual dynamic programming in problems with multiple near-optimal solutions. Water Resources Research, 52 (5). pp. 4151-4163. ISSN 0043-1397
Abstract
Stochastic dual dynamic programming (SDDP) is one of the few algorithmic solutions available to optimize large‐scale water resources systems while explicitly considering uncertainty. This paper explores the consequences of, and proposes a solution to, the existence of multiple near‐optimal solutions (MNOS) when using SDDP for mid or long‐term river basin management. These issues arise when the optimization problem cannot be properly parametrized due to poorly defined and/or unavailable data sets. This work shows that when MNOS exists, (1) SDDP explores more than one solution trajectory in the same run, suggesting different decisions in distinct simulation years even for the same point in the state‐space, and (2) SDDP is shown to be very sensitive to even minimal variations of the problem setting, e.g., initial conditions—we call this “algorithmic chaos.” Results that exhibit such sensitivity are difficult to interpret. This work proposes a reoptimization method, which simulates system decisions by periodically applying cuts from one given year from the SDDP run. Simulation results obtained through this reoptimization approach are steady state solutions, meaning that their probability distributions are stable from year to year.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2016 American Geophysical Union. This is an author-produced version of a paper subsequently published in Water Resources Research. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | stochastic dual dynamic programming; year‐periodic reoptimization; limited data availability; multiple near‐optimal solutions; Zambezi River Basin; chaos |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 13 Aug 2019 10:27 |
Last Modified: | 13 Aug 2019 10:54 |
Status: | Published |
Publisher: | American Geophysical Union |
Refereed: | Yes |
Identification Number: | 10.1002/2016wr018608 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:149616 |