Mathematical Programming

, Volume 26, Issue 2, pp 190–212 | Cite as

Truncated-newtono algorithms for large-scale unconstrained optimization

  • Ron S. Dembo
  • Trond Steihaug
Article

Abstract

We present an algorithm for large-scale unconstrained optimization based onNewton's method. In large-scale optimization, solving the Newton equations at each iteration can be expensive and may not be justified when far from a solution. Instead, an inaccurate solution to the Newton equations is computed using a conjugate gradient method. The resulting algorithm is shown to have strong convergence properties and has the unusual feature that the asymptotic convergence rate is a user specified parameter which can be set to anything between linear and quadratic convergence. Some numerical results on a 916 vriable test problem are given. Finally, we contrast the computational behavior of our algorithm with Newton's method and that of a nonlinear conjugate gradient algorithm.

Key words

Unconstrained Optimization Modified Newton Methods Conjugate Gradient Algorithms 

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Copyright information

© North-Holland Publishing Company 1983

Authors and Affiliations

  • Ron S. Dembo
    • 1
  • Trond Steihaug
    • 2
  1. 1.School of Organization and ManagementYale UniversityNew HavenUSA
  2. 2.Department of Mathematical SciencesRice UniversityHoustonUSA

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