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M. L'opez

6 papers hereh-index 334 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • middle author4
  • last author1

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • math.OC4
  • math.DS2
same name
  • M. L'opez — 44 papers, h 43
  • M. L'opez — 2 papers, h 3
  • M. L'opez — 2 papers, h 7
  • M. L'opez — 2 papers, h 2
  • M. L'opez — 2 papers
  • M. L'opez — 1 paper, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162019
collaborators
Showing math.OCShow all

4 papers · 1 filter

math.OC2019

Subdifferentials and Stability Analysis of Feasible Set and Pareto Front Mappings in Linear Multiobjective Optimization

María J. Cánovas, Marco A. López, Boris Mordukhovich +1

The paper concerns multiobjective linear optimization problems in R^n that are parameterized with respect to the right-hand side perturbations of inequality constraints. Our focus…

math.OC2019

Lipschitz modulus of linear and convex systems with the Hausdorff metric

Gerald Beer, María J. Cánovas, Marco A. López +1

This paper analyzes the Lipschitz behavior of the feasible set in two parametric settings, associated with linear and convex systems in R^n. To start with, we deal with the paramet…

math.OC2018

Characterizations of robust and stable duality for linearly perturbed uncertain optimization problems

Nguyen Dinh, Miguel A. Goberna, Marco A. López +1

We introduce a robust optimization model consisting in a family of perturbation functions giving rise to certain pairs of dual optimization problems in which the dual variable depe…

math.OC2016

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 F, from a decision space X to an objective space Y, is "min…

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