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...

Full description

Saved in:

Bibliographic Details
Published in:	Computational optimization and applications Vol. 88; no. 3; pp. 819 - 847
Main Authors:	Laguel, Yassine, Malick, Jérôme, van Ackooij, Wim
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.07.2024 Springer Nature B.V
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!