期刊
OPTIMIZATION LETTERS
卷 9, 期 7, 页码 1283-1295出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s11590-015-0854-y
关键词
Stochastic programming; Joint probabilistic constraints; 0-1 quadratic program; Copula theory; Semidefinite programming
资金
- Fondation Mathematiques Jacques Hadamard, PGMO/IROE [2012-042H]
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.
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