Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming

Abstract

The purpose of this paper is to describe a Generalized Reduced Gradient (GRG) algorithm for nonlinear programming, its implementation as a FORTRAN program for solving small to medium size problems, and some computational results. Our focus is more on the software implementation of the algorithm than on its mathematical properties. This is in line with the premise that robust, efficient, easy to use NLP software must be written and made accessible if nonlinear programming is to progress, both in theory and in practice.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1976
Accession Number
ADA025724

Entities

People

  • A. D. Waren
  • Arvind Jain
  • L. S. Lasdon
  • Margery Ratner

Organizations

  • Stanford University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Computations
  • Computer Programming
  • Direction Finding
  • Electric Power
  • Electric Power Distribution
  • Equations
  • Extrapolation
  • Iterations
  • Mathematical Programming
  • Military Research
  • Natural Language Processing
  • Nonlinear Programming
  • Operations Research
  • Power Distribution
  • Test And Evaluation

Fields of Study

  • Computer science
  • Mathematics

Readers

  • Computer Science.
  • Operations Research