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Vectorization is a technique that replaces a set-valued optimization problem with a vector optimization problem. In this work, by using an extension of Gerstewitz function [1], a vectorizing function is defined to replace a given set-valued…

Optimization and Control · Mathematics 2017-06-09 Emrah Karaman , İlknur Atasever Güvenç , Mustafa Soyertem , Didem Tozkan , Mahide Küçük , Yalçın Küçük

In this paper, we study a solution approach for set optimization problems with respect to the lower set less relation. This approach can serve as a base for numerically solving set optimization problems by using established solvers from…

Optimization and Control · Mathematics 2021-07-27 Gabriele Eichfelder , Ernest Quintana , Stefan Rocktäschel

In this paper, we remark on the published paper "Treatment of Set-Valued Robustness via Separation and Scalarization" [1], which deals with the robust solution to an uncertain constrained set-valued optimization problem via scalarization…

Optimization and Control · Mathematics 2025-11-04 Abhik Digar , Kuntal Som

In this paper, vector optimization is considered in the framework of decision making and optimization in general spaces. Interdependencies between domination structures in decision making and domination sets in vector optimization are…

Optimization and Control · Mathematics 2017-12-06 Petra Weidner

In the literature, necessary and sufficient conditions in terms of variational inequalities are introduced to characterize minimizers of convex set valued functions with values in a conlinear space. Similar results are proved for a weaker…

Optimization and Control · Mathematics 2016-12-02 Giovanni P. Crespi , Carola Schrage

We consider a multiobjective bilevel optimization problem with vector-valued upper- and lower-level objective functions. Such problems have attracted a lot of interest in recent years. However, so far, scalarization has appeared to be the…

Optimization and Control · Mathematics 2022-01-05 Lahoussine Lafhim , Alain Zemkoho

In this paper, we propose a Newton method for unconstrained set optimization problems to find its weakly minimal solutions with respect to lower set-less ordering. The objective function of the problem under consideration is given by…

Optimization and Control · Mathematics 2024-10-01 Debdas Ghosh , Anshika , Qamrul Hasan Ansari , Xiaopeng Zhao

In this paper, we study a first order solution method for a particular class of set optimization problems where the solution concept is given by the set approach. We consider the case in which the set-valued objective mapping is identified…

Optimization and Control · Mathematics 2021-07-27 Gemayqzel Bouza , Ernest Quintana , Christiane Tammer

Since the seminal papers by Giannessi, an interesting topic in vector optimization has been the characterization of (weak) efficiency thorough Minty and Stampacchia type variational inequalities. Several results have been proved to extend…

Optimization and Control · Mathematics 2016-12-02 Giovanni P. Crespi , Carola Schrage

In this paper, we consider set optimization problems where the solution concept is given by the set approach. Specifically, we deal with the lower less and the upper less set relations. First, we derive the convexity and Lipschitzianity of…

Optimization and Control · Mathematics 2021-07-28 Gemayqzel Bouza , Ernest Quintana , Christiane Tammer , Vu Anh Tuan

Scalarization in vector optimization is essentially based on the minimization of Gerstewitz functionals. In this paper, the minimizer sets of Gerstewitz functionals are investigated. Conditions are given under which such a set is nonempty…

Optimization and Control · Mathematics 2017-04-28 Petra Weidner

In this paper, we provide a new scheme for approximating the weakly efficient solution set for a class of vector optimization problems with rational objectives over a feasible set defined by finitely many polynomial inequalities. More…

Optimization and Control · Mathematics 2022-05-26 Feng Guo , Liguo Jiao

In this article, we develop a trust-region technique to find critical points of unconstrained set optimization problems with the objective set-valued map defined by finitely many twice continuously differentiable functions. The technique is…

Optimization and Control · Mathematics 2025-09-10 Suprova Ghosh , Debdas Ghosh , Christiane Tammer , Xiaopeng Zhao

We study the approximation of general multiobjective optimization problems with the help of scalarizations. Existing results state that multiobjective minimization problems can be approximated well by norm-based scalarizations. However, for…

Optimization and Control · Mathematics 2023-05-25 Stephan Helfrich , Arne Herzel , Stefan Ruzika , Clemens Thielen

Set- and vector-valued optimization problems can be re-formulated as complete lattice-valued problems. This has several advantages, one of which is the existence of a clear-cut solution concept which includes the attainment as the infimum…

Optimization and Control · Mathematics 2020-07-14 Andreas H Hamel , Frank Heyde , Daniela Visetti

Optimization models with non-convex constraints arise in many tasks in machine learning, e.g., learning with fairness constraints or Neyman-Pearson classification with non-convex loss. Although many efficient methods have been developed…

Optimization and Control · Mathematics 2023-03-24 Runchao Ma , Qihang Lin , Tianbao Yang

We determine the power of the weighted sum scalarization with respect to the computation of approximations for general multiobjective minimization and maximization problems. Additionally, we introduce a new multi-factor notion of…

Data Structures and Algorithms · Computer Science 2021-12-15 Cristina Bazgan , Stefan Ruzika , Clemens Thielen , Daniel Vanderpooten

In this paper, we investigate the nonemptiness of weak Pareto efficient solution set for a class of nonsmooth vector optimization problems on a nonempty closed constraint set without any boundedness and convexity assumptions. First, we…

Optimization and Control · Mathematics 2024-08-09 Danyang Liu , Jun Li , Giandomenico Mastroeni

Over the years, several classes of scalarization techniques in optimization have been introduced and employed in deriving separation theorems, optimality conditions and algorithms. In this paper, we study the relationships between some of…

Optimization and Control · Mathematics 2021-07-27 Gemayqzel Bouza , Ernest Quintana , Christiane Tammer

Scalarizing functions have been widely used to convert a multiobjective optimization problem into a single objective optimization problem. However, their use in solving (computationally) expensive multi- and many-objective optimization…

Machine Learning · Computer Science 2019-04-12 Tinkle Chugh
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