期刊
ACM TRANSACTIONS ON MATHEMATICAL SOFTWARE
卷 32, 期 1, 页码 113-137出版社
ASSOC COMPUTING MACHINERY
DOI: 10.1145/1132973.1132979
关键词
algorithms; conjugate gradient method; convergence; line search; unconstrained optimization; Wolfe conditions
Recently, a new nonlinear conjugate gradient scheme was developed which satisfies the descent condition g(k)(inverted perpendicular)dk <= - 7/8 parallel to g(k)parallel to(2) and which is globally convergent whenever the line search fulfills the Wolfe conditions. This article studies the convergence behavior of the algorithm; extensive numerical tests and comparisons with other methods for large-scale unconstrained optimization are given.
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