Quadratic two-stage stochastic optimization with coherent measures of risk
A new scheme to cope with two-stage stochastic optimization problems uses a risk measure as the objective function of the recourse action, where the risk measure is defined as the worst-case expected values over a set of constrained distributions. This paper develops an approach to deal with the cas...
| Main Authors: | , , |
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| Format: | Journal Article |
| Published: |
Springer
2017
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| Online Access: | http://purl.org/au-research/grants/arc/DP160102819 http://hdl.handle.net/20.500.11937/52156 |
| _version_ | 1848758859398643712 |
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| author | Sun, Jie Liao, L. Rodrigues, B. |
| author_facet | Sun, Jie Liao, L. Rodrigues, B. |
| author_sort | Sun, Jie |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | A new scheme to cope with two-stage stochastic optimization problems uses a risk measure as the objective function of the recourse action, where the risk measure is defined as the worst-case expected values over a set of constrained distributions. This paper develops an approach to deal with the case where both the first and second stage objective functions are convex linear-quadratic. It is shown that under a standard set of regularity assumptions, this two-stage quadratic stochastic optimization problem with measures of risk is equivalent to a conic optimization problem that can be solved in polynomial time. |
| first_indexed | 2025-11-14T09:50:41Z |
| format | Journal Article |
| id | curtin-20.500.11937-52156 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:50:41Z |
| publishDate | 2017 |
| publisher | Springer |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-521562019-02-19T05:36:18Z Quadratic two-stage stochastic optimization with coherent measures of risk Sun, Jie Liao, L. Rodrigues, B. A new scheme to cope with two-stage stochastic optimization problems uses a risk measure as the objective function of the recourse action, where the risk measure is defined as the worst-case expected values over a set of constrained distributions. This paper develops an approach to deal with the case where both the first and second stage objective functions are convex linear-quadratic. It is shown that under a standard set of regularity assumptions, this two-stage quadratic stochastic optimization problem with measures of risk is equivalent to a conic optimization problem that can be solved in polynomial time. 2017 Journal Article http://hdl.handle.net/20.500.11937/52156 10.1007/s10107-017-1131-x http://purl.org/au-research/grants/arc/DP160102819 Springer fulltext |
| spellingShingle | Sun, Jie Liao, L. Rodrigues, B. Quadratic two-stage stochastic optimization with coherent measures of risk |
| title | Quadratic two-stage stochastic optimization with coherent measures of risk |
| title_full | Quadratic two-stage stochastic optimization with coherent measures of risk |
| title_fullStr | Quadratic two-stage stochastic optimization with coherent measures of risk |
| title_full_unstemmed | Quadratic two-stage stochastic optimization with coherent measures of risk |
| title_short | Quadratic two-stage stochastic optimization with coherent measures of risk |
| title_sort | quadratic two-stage stochastic optimization with coherent measures of risk |
| url | http://purl.org/au-research/grants/arc/DP160102819 http://hdl.handle.net/20.500.11937/52156 |