Proceedings of the Centre for Mathematics and its Applications

Lagrangian conditions for a minimax

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Abstract

A general approach is given to Lagrangian necessary conditions for a minimax problem, The necessary conditions become sufficient for a mini max under extra hypotheses, with either concave/convex or invex functions, and restrictions on the constraints. A minimax is shown to relate to a weak minimum of a vector function. The sensitivity of a minimax value to a perturbation is related to the gradient of a Lagrangian function with respect to the parameter.

Article information

Source
Workshop/Miniconference on Functional Analysis and Optimization. Simon Fitzpatrick and John Giles, eds. Proceedings of the Centre for Mathematical Analysis, v. 20. (Canberra AUS: Centre for Mathematics and its Applications, Mathematical Sciences Institute, The Australian National University, 1988), 24-33

Dates
First available in Project Euclid: 18 November 2014

Permanent link to this document
https://projecteuclid.org/ euclid.pcma/1416340099

Mathematical Reviews number (MathSciNet)
MR1009590

Zentralblatt MATH identifier
0674.90086

Citation

Lagrangian conditions for a minimax. Workshop/Miniconference on Functional Analysis and Optimization, 24--33, Centre for Mathematics and its Applications, Mathematical Sciences Institute, The Australian National University, Canberra AUS, 1988. https://projecteuclid.org/euclid.pcma/1416340099


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