A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
Kernel function based interior-point methods for horizontal linear complementarity problems
2013
Journal of Inequalities and Applications
It is well known that each kernel function defines an interior-point algorithm. In this paper we propose new classes of kernel functions whose form is different from known kernel functions and define interior-point methods (IPMs) based on these functions whose barrier term is exponential power of exponential functions for P * (κ)-horizontal linear complementarity problems (HLCPs). New search directions and proximity measures are defined by these kernel functions. We obtain so far the best known
doi:10.1186/1029-242x-2013-215
fatcat:ia56lahpijgihpvjxcxztg6m2i