Add to ORKGAbstract. In this paper, Mond-Weir type duality results for a uncertain multiobjective robust optimization problem are given under generalized invexity assumptions. Also, weak vector saddle-point theorems are ob-tained under convexity assumptions. 1
This article focuses on optimality conditions for a robust fractional interval-valued optimization p...
In this paper, Antczak's -approximation approach is used to prove the equivalence between optima of ...
In this paper, a generalization of convexity is considered in the case of multiobjective optimizatio...
Robust optimization has come out to be a potent approach to study mathematical problems with data un...
The paper deals with optimization problems with uncertain constraints and linear perturbations of th...
In this paper, we employ a fuzzy optimality condition for the Frechet subdifferential and some advan...
In this paper a vector optimization problem (VOP) is considered where each component of objective an...
Duality theory is important in finding solutions to optimization problems. For example, in linear pr...
We formulate some basic properties of strict approximate solutions, or strict ε-solutions, of convex...
We propose four different duality problems for a vector optimization program with a set constraint, ...
This paper deals with the robust strong duality for nonconvex optimization problem with the data unc...
The multiobjective optimization model studied in this paper deals with simultaneous minimization of ...
Lagrangian duality in set optimization with an application to robust multiobjective optimization. We...
Robust bi-level programming problems are a newborn branch of optimization theory. In this study, we ...
This paper considers an uncertain convex optimization problem, posed in a locally convex decision sp...
This article focuses on optimality conditions for a robust fractional interval-valued optimization p...
In this paper, Antczak's -approximation approach is used to prove the equivalence between optima of ...
In this paper, a generalization of convexity is considered in the case of multiobjective optimizatio...
Robust optimization has come out to be a potent approach to study mathematical problems with data un...
The paper deals with optimization problems with uncertain constraints and linear perturbations of th...
In this paper, we employ a fuzzy optimality condition for the Frechet subdifferential and some advan...
In this paper a vector optimization problem (VOP) is considered where each component of objective an...
Duality theory is important in finding solutions to optimization problems. For example, in linear pr...
We formulate some basic properties of strict approximate solutions, or strict ε-solutions, of convex...
We propose four different duality problems for a vector optimization program with a set constraint, ...
This paper deals with the robust strong duality for nonconvex optimization problem with the data unc...
The multiobjective optimization model studied in this paper deals with simultaneous minimization of ...
Lagrangian duality in set optimization with an application to robust multiobjective optimization. We...
Robust bi-level programming problems are a newborn branch of optimization theory. In this study, we ...
This paper considers an uncertain convex optimization problem, posed in a locally convex decision sp...
This article focuses on optimality conditions for a robust fractional interval-valued optimization p...
In this paper, Antczak's -approximation approach is used to prove the equivalence between optima of ...
In this paper, a generalization of convexity is considered in the case of multiobjective optimizatio...