a path following interior-point algorithm for semidefinite optimization problem based on new kernel function

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 $o(6(m+1)^{frac{3m+4}{2(m+1)}}psi _{0}^{frac{m+2}{2(m+1)}}frac{1}{theta }log frac{nmu ^{0}}{varepsilon })$, where $m>4$.