Unified Analysis of Kernel-Based Interior-Point Methods for P *(κ)-LCP

G. Lesaja, C. Roos

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Abstract

We present an interior-point method for the P*(κ)- linear complementarity problem (LCP) that is based on barrier functions which are defined by a large class of univariate functions called eligible kernel functions. This class is fairly general and includes the classical logarithmic function and the self-regular functions, as well as many non-self-regular functions as special cases. We provide a unified analysis of the method and give a general scheme on how to calculate the iteration bounds for the entire class. We also calculate the iteration bounds of both long-step and short-step versions of the method for several specific eligible kernel functions. For some of them we match the best known iteration bounds for the long-step method, while for the short-step method the iteration bounds are of the same order of magnitude. As far as we know, this is the first paper that provides a unified approach and comprehensive treatment of interior-point methods for P * (κ)-LCPs based on the entire class of eligible kernel functions.

Original languageAmerican English
JournalSIAM Journal on Optimization
Volume20
DOIs
StatePublished - Jan 1 2011

Keywords

  • Interior-point method
  • Kernel functions
  • Linear complementarity problem
  • P*(K)-matrix
  • Polynomial complexity

DC Disciplines

  • Education
  • Mathematics

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