Characterization of Highly Robust Solutions in Multi-Objective Programming in Banach Spaces

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Hauptverfasser: Rahimi, Morteza, Soleimani-damaneh, Majid
Format: Preprint
Veröffentlicht: 2025
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author Rahimi, Morteza
Soleimani-damaneh, Majid
author_facet Rahimi, Morteza
Soleimani-damaneh, Majid
contents This paper delves into the challenging issues in uncertain multi-objective optimization, where uncertainty permeates nonsmooth nonconvex objective and constraint functions. In this context, we investigate highly robust (weakly efficient) solutions, a solution concept defined by efficiency across all scenarios. Our exploration reveals important relationships between highly robust solutions and other robustness notions, including set-based and worst-case notions, as well as connections with proper and isolated efficiency. Leveraging modern techniques from variational analysis, we establish necessary and sufficient optimality conditions for these solutions. Moreover, we explore the robustness of multi-objective optimization problems in the face of various uncertain sets, such as ball, ellipsoidal, and polyhedral sets.
format Preprint
id arxiv_https___arxiv_org_abs_2501_06640
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Characterization of Highly Robust Solutions in Multi-Objective Programming in Banach Spaces
Rahimi, Morteza
Soleimani-damaneh, Majid
Optimization and Control
90C29, 90C17, 90C46
This paper delves into the challenging issues in uncertain multi-objective optimization, where uncertainty permeates nonsmooth nonconvex objective and constraint functions. In this context, we investigate highly robust (weakly efficient) solutions, a solution concept defined by efficiency across all scenarios. Our exploration reveals important relationships between highly robust solutions and other robustness notions, including set-based and worst-case notions, as well as connections with proper and isolated efficiency. Leveraging modern techniques from variational analysis, we establish necessary and sufficient optimality conditions for these solutions. Moreover, we explore the robustness of multi-objective optimization problems in the face of various uncertain sets, such as ball, ellipsoidal, and polyhedral sets.
title Characterization of Highly Robust Solutions in Multi-Objective Programming in Banach Spaces
topic Optimization and Control
90C29, 90C17, 90C46
url https://arxiv.org/abs/2501.06640