Journal of Optimization Theory and Applications

, Volume 160, Issue 1, pp 111–126 | Cite as

Calmness of the Argmin Mapping in Linear Semi-Infinite Optimization

  • M. J. Cánovas
  • A. Hantoute
  • J. Parra
  • F. J. Toledo
Article

Abstract

This paper characterizes the calmness property of the argmin mapping in the framework of linear semi-infinite optimization problems under canonical perturbations; i.e., continuous perturbations of the right-hand side of the constraints (inequalities) together with perturbations of the objective function coefficient vector. This characterization is new for semi-infinite problems without requiring uniqueness of minimizers. For ordinary (finitely constrained) linear programs, the calmness of the argmin mapping always holds, since its graph is piecewise polyhedral (as a consequence of a classical result by Robinson). Moreover, the so-called isolated calmness (corresponding to the case of unique optimal solution for the nominal problem) has been previously characterized. As a key tool in this paper, we appeal to a certain supremum function associated with our nominal problem, not involving problems in a neighborhood, which is related to (sub)level sets. The main result establishes that, under Slater constraint qualification, perturbations of the objective function are negligible when characterizing the calmness of the argmin mapping. This result also states that the calmness of the argmin mapping is equivalent to the calmness of the level set mapping.

Keywords

Calmness Local error bounds Variational analysis Semi-infinite programming Linear programming 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • M. J. Cánovas
    • 1
  • A. Hantoute
    • 2
  • J. Parra
    • 1
  • F. J. Toledo
    • 1
  1. 1.Center of Operations ResearchMiguel Hernández University of ElcheElche (Alicante)Spain
  2. 2.Departamento de Ingeniería Matemática, Centro de Modelamiento Matemático (CMM)Universidad de ChileSantiagoChile

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