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...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2018
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/lkcsb_research/5155 https://ink.library.smu.edu.sg/context/lkcsb_research/article/6154/viewcontent/QuadraticTwo_stageStochasticOptimizationCoherent_2017_afv.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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. |
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