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.
Information
Published: 1 January 1988
First available in Project Euclid: 18 November 2014
zbMATH: 0674.90086
MathSciNet: MR1009590
Rights: Copyright © 1988, Centre for Mathematics and its Applications, Mathematical Sciences Institute, The Australian National University. This book is copyright. Apart from any fair dealing for the purpose of private study, research, criticism or review as permitted under the Copyright Act, no part may be reproduced by any process without permission. Inquiries should be made to the publisher.
