Name
Abstract | ||
|---|---|---|
We study the discrete optimization problem under the distributionally robust framework. We optimize the Entropic Value-at-Risk, which is a coherent risk measure and is also known as Bernstein approximation for the chance constraint. We propose an efficient approximation algorithm to resolve the problem via solving a sequence of nominal problems. The computational results show that the number of nominal problems required to be solved is small under various distributional information sets. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1016/j.orl.2014.09.004 | Operations Research Letters |
Keywords | Field | DocType |
Robust optimization,Discrete optimization,Coherent risk measure | Coherent risk measure,Approximation algorithm,Combinatorics,Mathematical optimization,Robust optimization,Discrete optimization,Discrete optimization problem,Optimization problem,Mathematics,Entropic value at risk | Journal |
Volume | Issue | ISSN |
42 | 8 | 0167-6377 |
Citations | PageRank | References |
1 | 0.36 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel Zhuoyu Long | 1 | 11 | 2.22 |
| Jin Qi | 2 | 31 | 2.25 |