Optimality Conditions in DC-Constrained Mathematical Programming Problems

被引：0
|
作者：
Rafael Correa
Marco A. López
Pedro Pérez-Aros
机构：
[1] Universidad de O’Higgins,Department of Mathematics
[2] DIM-CMM of Universidad de Chile,Centre for Informatics and Applied Optimization
[3] University of Alicante,Instituto de Ciencias de la Ingeniería
[4] Federation University Australia,undefined
[5] Universidad de O’Higgins,undefined
来源：
Journal of Optimization Theory and Applications | 2023年 / 198卷
关键词：
DC functions; DC-constrained programming; Conic programming; Infinite programming; Stochastic programming; Semi-definite programming; Supremum function; Primary: 90C30; 90C34; 90C26;
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学科分类号：
摘要：
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.
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页码：1191 / 1225
页数：34
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