Algorithmic Approximation of Optimal Value Differential Stability Bounds in Nonlinear Programming,

Abstract

The data needed to calculate the sensitivity to data perturbations of the solution and optimal value of a mathematical program are available as by-products of many solution. Fiacco demonstrated this is developing a penalty function technque for approximating the parameter derivatives of a solution for quite general perturbed non-linear programs. Armacost and Mylander used this to advantage in making available the routine calculation of sensitivity information as part of a computer code for the Sequential Unconstrained Minimization Technique (SUMT).

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1981
Accession Number
ADA110545

Entities

People

  • William P. Hutzler

Organizations

  • RAND Corporation

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Convex Programming
  • Convex Sets
  • Directional
  • Evolutionary Algorithms
  • Inequalities
  • Linear Programming
  • Mathematical Programming
  • Nonlinear Programming
  • Numbers
  • Optimization
  • Perturbations
  • Qualifications
  • Sensitivity
  • Sequences

Readers

  • Calculus or Mathematical Analysis
  • Operations Research