Title :
A parallel processing multi-coordinate descent method with line search for a class of large-scale optimization-algorithm and convergence
Author_Institution :
Dept. of Control Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
Abstract :
An efficient parallel processing multi-coordinate descent method with line search is proposed for the large-scale unconstrained optimization problems with sparse structure. Its convergence is proved, and it is noted that its efficiency is obvious from its inherent properties. A trivial application of the proposed algorithm is the large-scale power system static-state estimation problem
Keywords :
convergence of numerical methods; large-scale systems; optimisation; parallel algorithms; power system analysis computing; search problems; state estimation; convergence; large-scale optimization; large-scale power system static-state estimation; line search; parallel algorithms; parallel processing multi-coordinate descent method; power system analysis computing; sparse structure; unconstrained optimization; Control engineering; Convergence; Graph theory; Large-scale systems; Optimization methods; Parallel processing; Power systems; Search methods; State estimation;
Conference_Titel :
Decision and Control, 1991., Proceedings of the 30th IEEE Conference on
Conference_Location :
Brighton
Print_ISBN :
0-7803-0450-0
DOI :
10.1109/CDC.1991.261501
