1 citations · 2 across the 4 of their papers we have counts for
6 papers
Relaxed Lagrangian duality in convex infinite optimization: reverse strong duality and optimality
Nguyen Dinh, Miguel A. Goberna, Marco A. Lopez +1
We associate with each convex optimization problem posed on some locally convex space with an infinite index set T, and a given non-empty family H formed by finite subsets of T, a…
A Perturbation Approach to Vector Optimization Problems: Lagrange and Fenchel-Lagrange Duality
N. Dinh, D. H. Long
In this paper we study the general minimization vector problem (P), concerning a perturbation mapping, defined in locally convex Hausdorff topological vector spaces where the "WInf…
New Representations of Epigraphs of Conjugate Mappings and Lagrange, Fenchel-Lagrange Duality for Vector Optimization Problems
N. Dinh, D. H. Long
In this paper we concern the vector problem of the model: \begin{align*} ({\rm VP})\quad\qquad &\rm{WInf} \{F(x): x\in C,\; G(x)\in -S\}. \end{align*} where are locally c…
Simple Bilevel Programming and Extensions Part-II: Algorithms
Stephan Dempe, Nguyen Dinh, Joydeep Dutta +1
This article continues our study on simple bilevel and simple MPEC problems. In this article we focus on developing algorithms. We show how using the idea of a gap function one can…
Duality for the robust sum of functions
Nguyen Dinh, Miguel A. Goberna, Michel Volle
In this paper we associate with an infinite family of real extended functions defined on a locally convex space, a sum, called robust sum, which is always well-defined. We also ass…
Characterizing weak solutions for vector optimization problems
Nguyen Dinh, Miguel A. Goberna, Dang H. Long +1
This paper provides characterizations of the weak solutions of optimization problems where a given vector function from a decision space to an objective space , is "min…