On approximate solutions for robust semi-infinite multi-objective convex symmetric cone optimization

We present approximate solutions for the robust semi-infinite multi-objective convex symmetric cone programming problem. By using the robust optimization approach, we establish an approximate optimality theorem and approximate duality theorems for approximate solutions in convex symmetric cone optim...

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Veröffentlicht in:Positivity : an international journal devoted to the theory and applications of positivity in analysis Jg. 26; H. 5
Hauptverfasser: Alzalg, Baha, Oulha, Amira Achouak
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cham Springer International Publishing 01.11.2022
Springer Nature B.V
Schlagworte:
Algebra
Calculus of Variations and Optimal Control; Optimization
Econometrics
Fourier Analysis
Linear programming
Mathematics
Mathematics and Statistics
Multiple objective analysis
Operator Theory
Optimization
Potential Theory
Robustness
Theorems
90C20
Semi-infinite programming
Robust symmetric cone optimization
90C46
90C25
90C34
Approximate duality theorems
90C29
Multi-objective programming
Approximate optimality conditions
ISSN:1385-1292, 1572-9281
Online-Zugang:Volltext
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Zusammenfassung:We present approximate solutions for the robust semi-infinite multi-objective convex symmetric cone programming problem. By using the robust optimization approach, we establish an approximate optimality theorem and approximate duality theorems for approximate solutions in convex symmetric cone optimization problem involving infinitely many constraints to be satisfied and multiple objectives to be optimized simultaneously under the robust characteristic cone constraint qualification. We also give an example to illustrate the obtained results in an important special case, namely the robust semi-infinite multi-objective convex second-order cone program.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1385-1292
1572-9281
DOI:10.1007/s11117-022-00952-8