Exact Penalization in Stochastic Programming—Calmness and Constraint Qualification
Author
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-02-22
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Economics & Business Administration
Business Administration
Abstract EN
We deal with the conditions which ensure exact penalization in stochastic programming problems under finite discrete distributions.
We give several sufficient conditions for problem calmness including graph calmness, existence of an error bound, and generalized Mangasarian-Fromowitz constraint qualification.
We propose a new version of the theorem on asymptotic equivalence of local minimizers of chance constrained problems and problems with exact penalty objective.
We apply the theory to a problem with a stochastic vanishing constraint.
American Psychological Association (APA)
Branda, Martin. 2014. Exact Penalization in Stochastic Programming—Calmness and Constraint Qualification. Advances in Decision Sciences،Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-481494
Modern Language Association (MLA)
Branda, Martin. Exact Penalization in Stochastic Programming—Calmness and Constraint Qualification. Advances in Decision Sciences No. 2014 (2014), pp.1-6.
https://search.emarefa.net/detail/BIM-481494
American Medical Association (AMA)
Branda, Martin. Exact Penalization in Stochastic Programming—Calmness and Constraint Qualification. Advances in Decision Sciences. 2014. Vol. 2014, no. 2014, pp.1-6.
https://search.emarefa.net/detail/BIM-481494
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-481494