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A New Conjugate Gradient Method for Unconstrained Optimization Problems

Yongqiang He

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Abstract

In the ordinary circumstances,conjugate gradient method is the effective algorithm which solves the large-scale restraint question,different Selection of constructs different conjugate gradient method.We propose a new conjugate gradient method for unconstrained optimization problems by update and prove that method with wolf line search converges globally.

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What this paper is about

In the ordinary circumstances,conjugate gradient method is the effective algorithm which solves the large-scale restraint question,different Selection of constructs different conjugate gradient method.We propose a new conjugate gradient method for unconstrained optimization problems by update and prove that method with wolf line search converges globally.

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Available abstract

In the ordinary circumstances,conjugate gradient method is the effective algorithm which solves the large-scale restraint question,different Selection of constructs different conjugate gradient method.We propose a new conjugate gradient method for unconstrained optimization problems by update and prove that method with wolf line search converges globally.

Key concepts: Conjugate gradient method, Conjugate residual method, Nonlinear conjugate gradient method, Conjugate, Derivation of the conjugate gradient method, Gradient method, Mathematical optimization, Computer science

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