Title :
A New Primal-Dual Interior-Point Algorithm for Semidefinite Optimization
Author :
Lee, Yong-hoon ; Jin-Hee Jin ; Gyeong-Mi Cho
Author_Institution :
Dept. of Math., Pusan Nat. Univ., Busan, South Korea
Abstract :
We propose a new primal-dual interior-point algorithm for semidefinite optimization(SDO) based on an eligible barrier function. New search directions and proximity measures are proposed based on the barrier function. We show that the algorithm has O(√n log(n/ε)) and O(√n(log n)log(n/ε)) complexity results for small- and large-update methods, respectively. These are the best known complexity results for such methods.
Keywords :
computational complexity; optimisation; search problems; SDO; complexity results; eligible barrier function; large-update methods; primal-dual interior-point algorithm; proximity measures; search directions; semidefinite optimization; small-update methods; Complexity theory; Educational institutions; Kernel; Optimization; Symmetric matrices; Tin;
Conference_Titel :
Information Science and Applications (ICISA), 2014 International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4799-4443-9
DOI :
10.1109/ICISA.2014.6847334
