A parallel processing multi-coordinate descent method with line search for a class of large-scale optimization-algorithm and convergence

摘要

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.