An Arc Method for Nonlinear Programming.

Abstract

An algorithm using second derivatives for solving the optimization problem: minimize f(x) subject to (g subi) (x) > or = 0, i = 1,...,m where the (g sub i) are not necessarily linear is presented. The basic idea is to generate a sequence of feasible points with decreasing objective values by movement along piecewise, smooth, quadratic arcs. Cluster points of the sequence generated are shown to be second-order Kuhn-Tucker points. If the strict second order sufficiency conditions hold the rate of convergence is shown to be at least quadratic. (Author)

Document Details

Document Type
Technical Report
Publication Date
Feb 15, 1974
Accession Number
AD0776406

Entities

People

  • Garth Philip McCormick

Organizations

  • George Washington University

Tags

DTIC Thesaurus Topics

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

Fields of Study

  • Mathematics

Readers

  • Operations Research