Subdifferentials and Coderivatives of Efficient Point Multifunctions in Parametric Convex Vector Optimization

In this paper, by revisiting coderivative calculus rules for convex multifunctions in finite-dimensional spaces, we derive formulae for estimating/computing the basic subdifferential and the coderivative of the efficient point multifunction of parametric convex vector optimization problems. These re...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Journal of optimization theory and applications Ročník 202; číslo 2; s. 745 - 770
Hlavní autoři: An, Duong Thi Viet, Hung, Nguyen Huy, Van Tuyen, Nguyen
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.08.2024
Springer Nature B.V
Témata:
Applications of Mathematics
Banach spaces
Calculus
Calculus of Variations and Optimal Control; Optimization
Convex analysis
Engineering
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Optimization
Sensitivity analysis
Theory of Computation
90C31
Sensitivity analysis
49K40
49J52
90C25
Subdifferential
Coderivative
90C29
Parametric convex vector optimization
Efficient point multifunction
ISSN:0022-3239, 1573-2878
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In this paper, by revisiting coderivative calculus rules for convex multifunctions in finite-dimensional spaces, we derive formulae for estimating/computing the basic subdifferential and the coderivative of the efficient point multifunction of parametric convex vector optimization problems. These results are then applied to a broad class of conventional convex vector optimization problems with the presence of operator constraints and equilibrium ones. Examples are also designed to analyze and illustrate the obtained results.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0022-3239
1573-2878
DOI:10.1007/s10957-024-02446-x