dc.contributor.author | Aasgård, Ellen Krohn | |
dc.contributor.author | Skjelbred, Hans Ivar | |
dc.date.accessioned | 2020-03-20T11:14:31Z | |
dc.date.available | 2020-03-20T11:14:31Z | |
dc.date.created | 2019-12-20T13:04:19Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | Computational Management Science. 2019, 17 (1), 141-160. | en_US |
dc.identifier.issn | 1619-697X | |
dc.identifier.uri | https://hdl.handle.net/11250/2647799 | |
dc.description.abstract | In this paper, we show how progressive hedging may be used to solve stochastic programming problems that involve cross-scenario inequality constraints. In contrast, standard stochastic programs involve cross-scenario equality constraints that describe the non-anticipative nature of the optimal solution. The standard progressive hedging algorithm (PHA) iteratively manipulates the objective function coefficients of the scenario subproblems to reflect the costs of non-anticipativity and penalize deviations from a non-anticipative, aggregated solution. Our proposed algorithm follows the same principle, but works with cross-scenario inequality constraints. Specifically, we focus on the problem of determining optimal bids for hydropower producers that participate in wholesale electricity auctions. The cross-scenario inequality constraints arise from the fact that bids are required to be non-decreasing. We show that PHA for inequality constraints have the same convergence properties as standard PHA, and illustrate our algorithm with results for an instance of the hydropower bidding problem. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Springer Nature | en_US |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/deed.no | * |
dc.title | Progressive hedging for stochastic programs with cross scenario inequality constraints | en_US |
dc.type | Journal article | en_US |
dc.type | Peer reviewed | en_US |
dc.description.version | acceptedVersion | en_US |
dc.source.pagenumber | 141-160 | en_US |
dc.source.volume | 17 | en_US |
dc.source.journal | Computational Management Science | en_US |
dc.source.issue | 1 | en_US |
dc.identifier.doi | 10.1007/s10287-019-00359-z | |
dc.identifier.cristin | 1763341 | |
dc.relation.project | Norges forskningsråd: 255100 | en_US |
cristin.unitcode | 7548,50,0,0 | |
cristin.unitname | Energisystemer | |
cristin.ispublished | true | |
cristin.qualitycode | 1 | |