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A new large-update interior point algorithm for P ∗(κ) LCPs based on kernel functions
- Source :
-
Applied Mathematics & Computation . Nov2006, p1169-1183. 15p. - Publication Year :
- 2006
-
Abstract
- Abstract: In this paper we propose a new large-update primal-dual interior point algorithm for P ∗(κ) linear complementarity problems (LCPs). Recently, Peng et al. introduced self-regular barrier functions for primal-dual interior point methods (IPMs) for linear optimization (LO) problems and reduced the gap between the practical behavior of the algorithm and its theoretical worst case complexity. We introduce a new class of kernel functions which is not logarithmic barrier nor self-regular in the complexity analysis of interior point method (IPM) for P ∗(κ) linear complementarity problem (LCP). New search directions and proximity measures are proposed based on the kernel function. We showed that if a strictly feasible starting point is available, then the new large-update primal-dual interior point algorithms for solving P ∗(κ) LCPs have the polynomial complexity which is better than the classical large-update primal-dual algorithm based on the classical logarithmic barrier function. [Copyright &y& Elsevier]
- Subjects :
- *KERNEL functions
*COMPLEX variables
*GEOMETRIC function theory
*ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 00963003
- Database :
- Academic Search Index
- Journal :
- Applied Mathematics & Computation
- Publication Type :
- Academic Journal
- Accession number :
- 23350167
- Full Text :
- https://doi.org/10.1016/j.amc.2006.04.060