<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">El Amir Djeffal</style></author><author><style face="normal" font="default" size="100%">Lakhdar Djeffal</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A path following interior-point algorithm for semidefinite optimization problem based on new kernel function</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Mathematical Modeling</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://jmm.guilan.ac.ir/?_action=article&amp;au=10070&amp;_au=El+Amir++Djeffal</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">4</style></volume><pages><style face="normal" font="default" size="100%">35-58</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">In this paper, we deal to obtain some new complexity results for solving semidefinite optimization (SDO) problem by interior-point methods (IPMs). We define a new proximity function for the SDO by a new kernel function. Furthermore we formulate an algorithm for a primal dual interior-point method (IPM) for the SDO by using the proximity function and give its complexity analysis, and then we show that the worst-case iteration bound for our IPM is&amp;nbsp;O(6(m+1)3m+42(m+1)Ψm+22(m+1)01θlognμ0ε)O(6(m+1)3m+42(m+1)Ψ0m+22(m+1)1θlog⁡nμ0ε), where&amp;nbsp;m&amp;gt;4m&amp;gt;4.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record></records></xml>