Chance-constrained programs with convex underlying functions: a bilevel convex optimization perspective

Chance constraints are a valuable tool for the design of safe decisions in uncertain environments; they are used to model satisfaction of a constraint with a target probability. However, because of possible non-convexity and non-smoothness, optimizing over a chance constrained set is challenging. In...

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Vydané v:	Computational optimization and applications Ročník 88; číslo 3; s. 819 - 847
Hlavní autori:	Laguel, Yassine, Malick, Jérôme, van Ackooij, Wim
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.07.2024 Springer Nature B.V
Predmet:	Algorithms Approximation Constraints Convex analysis Convex and Discrete Geometry Convexity Management Science Mathematics Mathematics and Statistics Operations Research Operations Research/Decision Theory Optimization Random variables Smoothness Statistics DC programming Chance constraints Bilevel optimization Convex optimization Stochastic programming
ISSN:	0926-6003, 1573-2894
On-line prístup:	Získať plný text
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