Critical sets in parametric optimization
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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.
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- Critical sets in parametric optimization
Volume 34, Issue 3 , pp 333-353
- Cover Date
- Print ISSN
- Online ISSN
- Additional Links
- Generalized Critical Point
- Critical Point
- Linear Index
- Quadratic Index
- Kuhn-Tucker Set
- Mangasarian-Fromowitz Constraint Qualification
- Parametric Optimization
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