Abstract
We establish two algorithms of curved search method for unconstrained optimization in this paper. In these models, not only the general nonmonotonic strategy which was proposed by Grippo et al. [11] is adopted, but also some new nonmonotonic strategies are used. As for the usual curved search method, the global convergence and quadratic rate of convergence are proved for our models. The preliminary numerical experiments show that our methods are more efficient than the usual curved search method.
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