Computational Experience with Optimal Value Function and Lagrange Multiplier Sensitivity in NLP

Abstract

Sensitivity analysis in nonlinear programming is examined using the Sequential Unconstrained Minimization Technique. Particular emphasis is placed on the partial derivatives of the Lagrange multipliers and the optimal value function taken with respect to specified problem parameters, the estimation of which is based on recent developments by Armacost and Fiacco. The computational experience complements that previously reported by Armacost and Fiacco. An application of the sensitivity analysis to a large-scale, multi-item inventory model developed for the U.S. Navy is presented.

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Document Details

Document Type
Technical Report
Publication Date
May 10, 1976
Accession Number
ADA026374

Entities

People

  • Robert L. Armacost

Organizations

  • George Washington University

Tags

Communities of Interest

  • Advanced Electronics
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • California
  • Computer Programming
  • Computer Programs
  • Computers
  • Engineering
  • Engineers
  • Instructions
  • Inventory
  • Military Research
  • National Security
  • New York
  • Nonlinear Programming
  • Numerical Analysis
  • Security
  • Standards
  • United States

Readers

  • Operations Research
  • Systems Analysis and Design