Name
Abstract | ||
|---|---|---|
In this paper, we study 0–1 quadratic programs with joint probabilistic constraints. The row vectors of the constraint matrix are assumed to be normally distributed but are not supposed to be independent. We propose a mixed integer linear reformulation and provide an efficient semidefinite relaxation of the original problem. The dependence of the random vectors is handled by the means of copulas. Finally, numerical experiments are conducted to show the strength of our approach. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1007/s11590-015-0854-y | Optimization Letters |
Keywords | Field | DocType |
Stochastic programming, Joint probabilistic constraints, 0–1 quadratic program, Copula theory, Semidefinite programming | Second-order cone programming,Integer,Mathematical optimization,Quadratically constrained quadratic program,Quadratic equation,Probabilistic logic,Quadratic programming,Stochastic programming,Semidefinite programming,Mathematics | Journal |
Volume | Issue | ISSN |
9 | 7 | 1862-4480 |
Citations | PageRank | References |
4 | 0.45 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jianqiang Cheng | 1 | 72 | 9.66 |
| Michal Houda | 2 | 5 | 1.82 |
| Abdel Lisser | 3 | 168 | 29.93 |