Nonlinear Programming Sensitivity Analysis Results Using Strong Second Order Assumptions.

Abstract

Invoking conditions utilized to obtain numerous ideal results in nonlinear programming, this paper summarizes the development of a basis for calculating the first partial derivatives of a Kuhn-Tucker triple and the first and second partial derivatives of the optimal value function, with respect to problem parameters. In the context of prior results, a simpler but much more general derivation of the Kuhn-Tucker triple derivatives is presented, and a more concise formula for the Hessian of the optimal value function is given. Particularizations to the problems with right-hand-side constraint perturbations, no constraint perturbations and no constraints follow easily and are briefly treated. Further extensions and applications are indicated. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 26, 1978
Accession Number
ADA058633

Entities

People

  • Anthony V. Fiacco

Organizations

  • George Washington University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computational Science
  • Computations
  • Computer Programming
  • Convergence
  • Convex Programming
  • Engineering
  • Equations
  • Families (Human)
  • Lagrangian Functions
  • Linear Programming
  • Mathematical Programming
  • Nonlinear Programming
  • Notation
  • Optimization
  • Perturbations
  • Simplex Method

Fields of Study

  • Mathematics

Readers

  • Microwave Engineering.
  • Operations Research