Please use this identifier to cite or link to this item: https://doi.org/10.1287/opre.1070.0441
DC FieldValue
dc.titleA robust optimization perspective on stochastic programming
dc.contributor.authorChen, X.
dc.contributor.authorSim, M.
dc.contributor.authorSun, P.
dc.date.accessioned2013-10-09T03:25:37Z
dc.date.available2013-10-09T03:25:37Z
dc.date.issued2007
dc.identifier.citationChen, X., Sim, M., Sun, P. (2007). A robust optimization perspective on stochastic programming. Operations Research 55 (6) : 1058-1071. ScholarBank@NUS Repository. https://doi.org/10.1287/opre.1070.0441
dc.identifier.issn0030364X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/44052
dc.description.abstractIn this paper, we introduce an approach for constructing uncertainty sets for robust optimization using new deviation measures for random variables termed the forward and backward deviations. These deviation measures capture distributional asymmetry and lead to better approximations of chance constraints. Using a linear decision rule, we also propose a tractable approximation approach for solving a class of multistage chance-constrained stochastic linear optimization problems. An attractive feature of the framework is that we convert the original model into a second-order cone program, which is computationally tractable both in theory and in practice. We demonstrate the framework through an application of a project management problem with uncertain activity completion time. © 2007 INFORMS.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1287/opre.1070.0441
dc.sourceScopus
dc.subjectProgramming: stochastic
dc.typeArticle
dc.contributor.departmentDECISION SCIENCES
dc.description.doi10.1287/opre.1070.0441
dc.description.sourcetitleOperations Research
dc.description.volume55
dc.description.issue6
dc.description.page1058-1071
dc.description.codenOPREA
dc.identifier.isiut000251862400004
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

212
checked on May 19, 2022

WEB OF SCIENCETM
Citations

189
checked on May 19, 2022

Page view(s)

231
checked on May 12, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.