Second-Order Parametric Sensitivity Analysis in NLP and Estimates by Penalty Function Methods,

Abstract

Pursuing a number of theoretical results recently obtained by Fiacco, this paper continues the development of a basis for calculating first-order changes in a Kuhn-Tucker triple and second-order changes in the optimal value function of a class of general parametric nonlinear programming problems, with respect to a perturbation of the problem parameters. Exploiting problem structure, specific formulas are derived for calculating the first partial derivatives of a Kuhn-Tucker triple. Approximations to these quantities are obtained in parallel throughout, by way of an associated logarithmic-quadratic penalty function. Applications are indicated.

Document Details

Document Type
Technical Report
Publication Date
Dec 04, 1975
Accession Number
ADA022629

Entities

People

  • Anthony V. Fiacco
  • Robert L. Armacost

Organizations

  • George Washington University

Tags

DTIC Thesaurus Topics

  • Applied Mathematics
  • Computer Programming
  • Computing-Related Activities
  • Interdisciplinary Science
  • Mathematical Analysis
  • Mathematical Programming
  • Mathematics
  • Nonlinear Programming
  • Numerical Analysis
  • Numerical Methods And Procedures
  • Perturbations
  • Sensitivity

Fields of Study

  • Mathematics
  • Physics

Readers

  • Operations Research