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2016•Journal of applied mathematics & informaticsOpen access

A NONLINEAR CONJUGATE GRADIENT METHOD AND ITS GLOBAL CONVERGENCE ANALYSIS

Ajie Chu, Yixiao Su, Shouqiang Du

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Abstract

In this paper, we develop a new hybridization conjugate gradient method for solving the unconstrained optimization problem. Under mild assumptions, we get the sufficient descent property of the given method. The global convergence of the given method is also presented under the Wolfe-type line search and the general Wolfe line search. The numerical results show that the method is also efficient.

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In this paper, we develop a new hybridization conjugate gradient method for solving the unconstrained optimization problem. Under mild assumptions, we get the sufficient descent property of the given method. The global convergence of the given method is also presented under the Wolfe-type line search and the general Wolfe line search. The numerical results show that the method is also efficient.

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Available abstract

In this paper, we develop a new hybridization conjugate gradient method for solving the unconstrained optimization problem. Under mild assumptions, we get the sufficient descent property of the given method. The global convergence of the given method is also presented under the Wolfe-type line search and the general Wolfe line search. The numerical results show that the method is also efficient.

Key concepts: Nonlinear conjugate gradient method, Conjugate gradient method, Mathematics, Line search, Convergence (economics), Derivation of the conjugate gradient method, Conjugate residual method, Descent (aeronautics)

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