Armijo rule and strong wolfe line search in generalized newton method
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KünyeKetabci, S., Parandegan, M. ve Navidi, H. (2009). Armijo rule and strong wolfe line search in generalized newton method. Maltepe Üniversitesi. s. 350.
The line search method is one of the two fundamental strategies to solve unconstrained optimization problem that have been developed up to now. The second strategy is trust region method. In the line search method, the success of the algorithm not only depends on well-chosen search direction but also well-chosen step length. In this paper we compare the Armijo step size regulation and Strong Wolfe conditions in generalized Newton algorithm to minimizing a piecewise quadratic convex function. This function arises from dual exterior penalty problem for the problem of finding normal solution of the system of linear equalities. Numerical experience for systems which are selected in NETLIB indicates the behavior of the two inexact line searches differs markedly.
KaynakInternational Conference of Mathematical Sciences
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