Mathematical Programming

, Volume 107, Issue 3, pp 391–408 | Cite as

An interior algorithm for nonlinear optimization that combines line search and trust region steps

  • R.A. Waltz
  • J.L. Morales
  • J. Nocedal
  • D. Orban
Article

Abstract.

An interior-point method for nonlinear programming is presented. It enjoys the flexibility of switching between a line search method that computes steps by factoring the primal-dual equations and a trust region method that uses a conjugate gradient iteration. Steps computed by direct factorization are always tried first, but if they are deemed ineffective, a trust region iteration that guarantees progress toward stationarity is invoked. To demonstrate its effectiveness, the algorithm is implemented in the Knitro [6,28] software package and is extensively tested on a wide selection of test problems.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • R.A. Waltz
    • 1
  • J.L. Morales
    • 2
  • J. Nocedal
    • 1
  • D. Orban
    • 1
  1. 1.Department of Electrical and Computer EngineeringNorthwestern University 
  2. 2.Departamento de MatemáticasITAM México

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