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Central Region Method

  • Hans Frenk
  • Kees Roos
  • Tamás Terlaky
  • Shuzhong Zhang
Part of the Applied Optimization book series (APOP, volume 33)

Abstract

In this chapter, we discuss a modification of the standard path-following scheme that tends to speed up the global convergence. This modification, the central region method, generates iterates that do not really trace the central path, or at least not closely. In this way, it has a relatively large freedom of movement, and consequently the ability to take long steps. This makes it interesting to consider more sophisticated search directions. We propose a search direction that is built up in three phases, viz.
  1. 1.

    Initial centering,

     
  2. 2.

    Predictor,

     
  3. 3.

    Second order centrality corrector.

     

Keywords

Search Direction Step Length Linear Complementarity Problem SIAM Journal Interior Point Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2000

Authors and Affiliations

  • Hans Frenk
    • 1
  • Kees Roos
    • 2
  • Tamás Terlaky
    • 2
  • Shuzhong Zhang
    • 1
  1. 1.Erasmus UniversityRotterdamThe Netherlands
  2. 2.Delft University of TechnologyThe Netherlands

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