Minimax Problems, Saddle-Functions and Duality

Abstract

Minimax problems are fundamented to nonlinear programming, because of the way constraints can be represented using Lagrange multipliers. Better ways of solving minimax problems would lead thus lead to breakthroughs in solving most other problems of optimization. The dissertation opens a new avenue to the study of minimax problems by developing a theory of dual operations on saddle- functions convex-concave functions parallel to that already known for (purely) convex functions. Results are thereby obtained concerning minimax problems which are dual to each other. It is expected that these results will find computational applications analogous to those already acclaimed in the convex case, for instance in decomposition of large-scale problems.

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Document Details

Document Type
Technical Report
Publication Date
May 28, 1971
Accession Number
AD0741923

Entities

People

  • Lynn Mclinden

Organizations

  • University of Washington

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Algorithms
  • Calculus Of Variations
  • Convex Programming
  • Convex Sets
  • Differential Equations
  • Equations
  • Game Theory
  • Hypotheses
  • Identities
  • Linear Programming
  • Matrix Games
  • New York
  • Optimization
  • Simplex Method
  • Theorems
  • Theses
  • Topology

Readers

  • Operations Research
  • Systems Analysis and Design