Distributionally robust joint chance constraints with second-order moment information

We develop tractable semidefinite programming based approximations for distributionally robust individual and joint chance constraints, assuming that only the first- and second-order moments as well as the support of the uncertain parameters are given. It is known that robust chance constraints can...

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Vydané v:	Mathematical programming Ročník 137; číslo 1-2; s. 167 - 198
Hlavní autori:	Zymler, Steve, Kuhn, Daniel, Rustem, Berç
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin/Heidelberg Springer-Verlag 01.02.2013 Springer Nature B.V
Predmet:	Analysis Approximation Benchmarking Calculus of Variations and Optimal Control; Optimization Combinatorics Dynamic tests Full Length Paper Inequality Mathematical analysis Mathematical and Computational Physics Mathematical Methods in Physics Mathematical models Mathematics Mathematics and Statistics Mathematics of Computing Numerical Analysis Optimization Probability Probability distribution Programming Semidefinite programming Studies Theoretical Tightness 90C22 90C15
ISSN:	0025-5610, 1436-4646
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