Contributed Papers

Journal of Optimization Theory and Applications

, Volume 56, Issue 2, pp 245-255

First online:

Numerical experience with the truncated Newton method for unconstrained optimization

  • L. C. W. DixonAffiliated withNumerical Optimization Centre, Hatfield Polytechnic
  • , R. C. PriceAffiliated withNumerical Optimization Centre, Hatfield Polytechnic

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Abstract

The truncated Newton algorithm was devised by Dembo and Steihaug (Ref. 1) for solving large sparse unconstrained optimization problems. When far from a minimum, an accurate solution to the Newton equations may not be justified. Dembo's method solves these equations by the conjugate direction method, but truncates the iteration when a required degree of accuracy has been obtained. We present favorable numerical results obtained with the algorithm and compare them with existing codes for large-scale optimization.

Key Words

Unconstrained optimization truncated Newton method sparsity trust region