A Quadratically-Convergent Algorithm for General Nonlinear Programming Problems.

Abstract

The paper presents an algorithm for solving nonlinearly constrained programming problems. The algorithm reduces the original problem to a sequence of linearly-constrained minimization problems, for which efficient algorithms are available. A convergence theorem is given which states that if the process is started sufficiently close to a strict second-order Kuhn-Tucker point, then the sequence produced by the algorithm exists and converges R-quadratically to that point. (Author)

Document Details

Document Type
Technical Report
Publication Date
May 01, 1972
Accession Number
AD0744327

Entities

People

  • Stephen M. Robinson

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Convergence
  • Evolutionary Algorithms
  • Heuristic Methods
  • Mathematics
  • Nonlinear Programming
  • Sequences

Fields of Study

  • Mathematics

Readers

  • Operations Research