Please use this identifier to cite or link to this item: https://doi.org/10.1023/B:JOGO.0000015311.63755.01
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dc.titleA new decomposition technique in solving multistage stochastic linear programs by infeasible interior point methods
dc.contributor.authorLiu, X.
dc.contributor.authorSun, J.
dc.date.accessioned2013-10-09T06:19:16Z
dc.date.available2013-10-09T06:19:16Z
dc.date.issued2004
dc.identifier.citationLiu, X., Sun, J. (2004). A new decomposition technique in solving multistage stochastic linear programs by infeasible interior point methods. Journal of Global Optimization 28 (2) : 197-215. ScholarBank@NUS Repository. https://doi.org/10.1023/B:JOGO.0000015311.63755.01
dc.identifier.issn09255001
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/44230
dc.description.abstractMultistage stochastic linear programming (MSLP) is a powerful tool for making decisions under uncertainty. A deterministic equivalent problem of MSLP is a large-scale linear program with nonanticipativity constraints. Recently developed infeasible interior point methods are used to solve the resulting linear program. Technical problems arising from this approach include rank reduction and computation of search directions. The sparsity of the nonanticipativity constraints and the special structure of the problem are exploited by the interior point method. Preliminary numerical results are reported. The study shows that, by combining the infeasible interior point methods and specific decomposition techniques, it is possible to greatly improve the computability of multistage stochastic linear programs.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1023/B:JOGO.0000015311.63755.01
dc.sourceScopus
dc.subjectDecomposition
dc.subjectInfeasible primal-dual interior point method
dc.subjectScenario analysis
dc.subjectStochastic linear programs
dc.typeArticle
dc.contributor.departmentSINGAPORE-MIT ALLIANCE
dc.contributor.departmentDECISION SCIENCES
dc.description.doi10.1023/B:JOGO.0000015311.63755.01
dc.description.sourcetitleJournal of Global Optimization
dc.description.volume28
dc.description.issue2
dc.description.page197-215
dc.description.codenJGOPE
dc.identifier.isiut000188853400005
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