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dc.contributor.author Correa, R
dc.contributor.author López, MA
dc.contributor.author Pérez-Aros, P
dc.date.accessioned 2024-01-17T15:55:10Z
dc.date.available 2024-01-17T15:55:10Z
dc.date.issued 2023
dc.identifier.uri https://repositorio.uoh.cl/handle/611/732
dc.description.abstract This paper provides necessary and sufficient optimality conditions for abstract-constrained mathematical programming problems in locally convex spaces under new qualification conditions. Our approach exploits the geometrical properties of certain mappings, in particular their structure as difference of convex functions, and uses techniques of generalized differentiation (subdifferential and coderivative). It turns out that these tools can be used fruitfully out of the scope of Asplund spaces. Applications to infinite, stochastic and semi-definite programming are developed in separate sections.
dc.description.sponsorship CRUE-CSIC agreement
dc.description.sponsorship Springer Nature
dc.relation.uri http://dx.doi.org/10.1007/s10957-023-02260-x
dc.subject DC functions
dc.subject DC-constrained programming
dc.subject Conic programming
dc.subject Infinite programming
dc.subject Stochastic programming
dc.subject Semi-definite programming
dc.subject Supremum function
dc.title Optimality Conditions in DC-Constrained Mathematical Programming Problems
dc.type Artículo
uoh.revista JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
dc.identifier.doi 10.1007/s10957-023-02260-x
dc.citation.volume 198
dc.citation.issue 3
dc.identifier.orcid Perez-Aros, Pedro/0000-0002-8756-3011
uoh.indizacion Web of Science


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