Mathematical Programming

, Volume 34, Issue 3, pp 333–353

Critical sets in parametric optimization

  • H. Th. Jongen
  • P. Jonker
  • F. Twilt
Article

Abstract

We deal with one-parameter families of optimization problems in finite dimensions. The constraints are both of equality and inequality type. The concept of a ‘generalized critical point’ (g.c. point) is introduced. In particular, every local minimum, Kuhn-Tucker point, and point of Fritz John type is a g.c. point. Under fairly weak (even generic) conditions we study the set consisting of all g.c. points. Due to the parameter, the set is pieced together from one-dimensional manifolds. The points of can be divided into five (characteristic) types. The subset of ‘nondegenerate critical points’ (first type) is open and dense in (nondegenerate means: strict complementarity, nondegeneracy of the corresponding quadratic form and linear independence of the gradients of binding constraints). A nondegenerate critical point is completely characterized by means of four indices. The change of these indices along is presented. Finally, the Kuhn-Tucker subset of is studied in more detail, in particular in connection with the (failure of the) Mangasarian-Fromowitz constraint qualification.

Key words

Generalized Critical Point Critical Point Linear Index Quadratic Index Kuhn-Tucker Set Mangasarian-Fromowitz Constraint Qualification Parametric Optimization 

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Copyright information

© The Mathematical Programming Society, Inc. 1986

Authors and Affiliations

  • H. Th. Jongen
    • 1
  • P. Jonker
    • 1
  • F. Twilt
    • 1
  1. 1.Department of Applied MathematicsTwente University of TechnologyEnschedeThe Netherlands

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