A Successive Linear Programming Method and Its Convergence on Nonlinear Problems.

Abstract

Since Griffith and Stewart firstly proposed as successive linear programming method for solving general nonlinear programming problems, such methods have been widely used in practice because of their ease of implementation and their ability to deal with large scale problems. However, neither the original version, nor a more recent one contain convergence proofs possibly because of non-robustness of their algorithms. Using exact penalty functions and Levenberg Marquardtlike steps, an improved algorithm has been recently devised. In this paper, we give this modified SLP method a theoretical analysis and covergence proof, and thereby provide a sound basis for it. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1983
Accession Number
ADA126240

Entities

People

  • Jinlun Zhang

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Air Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Convergence
  • Convex Sets
  • Evolutionary Algorithms
  • Governments
  • Inequalities
  • Linear Programming
  • Nonlinear Programming
  • Optimization
  • Qualifications
  • Stationary
  • Theorems
  • United States
  • United States Government
  • Universities

Fields of Study

  • Computer science

Readers

  • Mathematical Modeling and Probability Theory.
  • Operations Research