| Summary: | 碩士 === 國立臺灣科技大學 === 工程技術研究所 === 82 === This paper introduced a new global strategy, the tensor dogleg
method, for unconstrained optimization, especially using tensor
methods. Tensor methods for unconstrained optimization were
first introduced by Schnabel and Chow [SIAM J.Opt.,21(1991),
pp.293-315]. They adopted line search method and two version of
trust region methods as global strategies, but these trust
region methods were either inefficient or too complicated.
Therefore, the software package, TENMIN, developed by Chow,
Eskow and Schnabel[To appear on ACM TOMS][SIAM J.Opt.,1993]
employed only the line search method as the global strategy. We
tested several different versions of our tensor dogleg
algorithm. Although the performance of each version of the
algorithm differs slightly, most of them perform better then
TENMIN. We finally introduced two tensor dogleg algorithm and
according the testing data, not only the number of iterations
but also the function evaluation, our algorithms are better
than the conventional method.
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