A path following interior-point algorithm for semidefinite optimization problem based on new kernel function
Author(s):
Abstract:
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 O(6(m)3m(m)Ψm(m)01θlognμ0ε), where m>4.
Language:
English
Published:
Journal of Mathematical Modeling, Volume:4 Issue: 1, Summer 2016
Pages:
35 to 58
https://www.magiran.com/p1616526