Optimality and duality for robust semi-infinite nonsmooth multiobjective fractional programming under Univexity

The idea behind proposing a robust model in this article is its relevance to real-world scenarios where uncertainty appears in optimization problems. This paper aims to analyze semi-infinite nonsmooth multiobjective fractional programming problem with data uncertainty. To address the nonsmoothness o...

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Veröffentlicht in:Journal of applied mathematics & computing Jg. 71; H. 5; S. 7463 - 7491
Hauptverfasser: Sachdev, Geeta, Bagri, Ritu, Agarwal, Divya
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2025
Springer Nature B.V
Schlagworte:
Computational Mathematics and Numerical Analysis
Efficiency
Linear programming
Mathematical and Computational Engineering
Mathematical programming
Mathematics
Mathematics and Statistics
Mathematics of Computing
Multiple objective analysis
Optimization
Original Research
Robustness
Theory of Computation
Uncertainty
Nonsmooth
90C46
Robust duality
Multiobjective programming
90C34
90C17
Semi-infinite
90C29
Fractional programming
ISSN:1598-5865, 1865-2085
Online-Zugang:Volltext
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Zusammenfassung:The idea behind proposing a robust model in this article is its relevance to real-world scenarios where uncertainty appears in optimization problems. This paper aims to analyze semi-infinite nonsmooth multiobjective fractional programming problem with data uncertainty. To address the nonsmoothness of functions, the functions involved are considered as directionally differentiable. Firstly, the robust necessary and sufficient optimality conditions are established under generalized univexity assumptions. For better comprehension of sufficiency results, an illustrative application is also provided. Further, a dual explored by a few authors: the Jagannathan type dual is formulated for the given primal problem. This dual has been explored due to its parametric form which can be solved with ease by a variety of computational approaches and hence, has potential applications in exploring various mathematical programming problems formulated in real life issues. Finally, the fundamental robust duality theorems namely weak, strong and strict converse duality are developed by employing the generalized univexity of the involved functions.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1598-5865
1865-2085
DOI:10.1007/s12190-025-02584-z