A model of distributionally robust two-stage stochastic convex programming with linear recourse
We consider distributionally robust two-stage stochastic convex programming problems, in which the recourse problem is linear. Other than analyzing these new models case by case for different ambiguity sets, we adopt a unified form of ambiguity sets proposed by Wiesemann, Kuhn and Sim, and extend th...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Published: |
Elsevier
2018
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| Online Access: | http://purl.org/au-research/grants/arc/DP160102819 http://hdl.handle.net/20.500.11937/67449 |
| _version_ | 1848761569076314112 |
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| author | Li, Bin Qian, X. Sun, Jie Teo, Kok Lay Yu, C. |
| author_facet | Li, Bin Qian, X. Sun, Jie Teo, Kok Lay Yu, C. |
| author_sort | Li, Bin |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | We consider distributionally robust two-stage stochastic convex programming problems, in which the recourse problem is linear. Other than analyzing these new models case by case for different ambiguity sets, we adopt a unified form of ambiguity sets proposed by Wiesemann, Kuhn and Sim, and extend their analysis from a single stochastic constraint to the two-stage stochastic programming setting. It is shown that under a standard set of regularity conditions, this class of problems can be converted to a conic optimization problem. Numerical results are presented to show the efficiency of the distributionally robust approach. |
| first_indexed | 2025-11-14T10:33:45Z |
| format | Journal Article |
| id | curtin-20.500.11937-67449 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:33:45Z |
| publishDate | 2018 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-674492023-04-26T05:14:48Z A model of distributionally robust two-stage stochastic convex programming with linear recourse Li, Bin Qian, X. Sun, Jie Teo, Kok Lay Yu, C. We consider distributionally robust two-stage stochastic convex programming problems, in which the recourse problem is linear. Other than analyzing these new models case by case for different ambiguity sets, we adopt a unified form of ambiguity sets proposed by Wiesemann, Kuhn and Sim, and extend their analysis from a single stochastic constraint to the two-stage stochastic programming setting. It is shown that under a standard set of regularity conditions, this class of problems can be converted to a conic optimization problem. Numerical results are presented to show the efficiency of the distributionally robust approach. 2018 Journal Article http://hdl.handle.net/20.500.11937/67449 10.1016/j.apm.2017.11.039 http://purl.org/au-research/grants/arc/DP160102819 Elsevier unknown |
| spellingShingle | Li, Bin Qian, X. Sun, Jie Teo, Kok Lay Yu, C. A model of distributionally robust two-stage stochastic convex programming with linear recourse |
| title | A model of distributionally robust two-stage stochastic convex programming with linear recourse |
| title_full | A model of distributionally robust two-stage stochastic convex programming with linear recourse |
| title_fullStr | A model of distributionally robust two-stage stochastic convex programming with linear recourse |
| title_full_unstemmed | A model of distributionally robust two-stage stochastic convex programming with linear recourse |
| title_short | A model of distributionally robust two-stage stochastic convex programming with linear recourse |
| title_sort | model of distributionally robust two-stage stochastic convex programming with linear recourse |
| url | http://purl.org/au-research/grants/arc/DP160102819 http://hdl.handle.net/20.500.11937/67449 |