A Modified Conjugate Gradient Algorithm for Unconstrained Nonlinear Optimization
A Modified Conjugate Gradient Algorithm for Unconstrained Nonlinear Optimization
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发表时间：
1975-12
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通讯作者：
A. Perry
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作者：
A. Perry
提出了一种改进的Fletcher-Reeves （FRCG）共轭梯度算法[3]。这种改进的结果比FRCG或PRCG （Polak-Ribiere共轭梯度算法[7,10]）的计算性能更稳定。我们将这种稳定的行为归因于本文提出的修改，该修改将准牛顿算法的一个最重要的特征（FRCG和PRCG中缺少这个特征）纳入共轭梯度过程，而不增加存储要求。我们将提出修改的动机，并通过一个令人鼓舞的计算结果来支持这些论点。
W E PRESENT a modification of the Fletcher-Reeves (FRCG) conjugate gradient algorithm [3]. This modification results in a more stable computational performance than the ones exhibited by either FRCG or PRCG (Polak-Ribiere conjugate gradient algorithm [7, 10]). We attribute this stable behavior to the modification proposed here, which incorporates one of the most important features of the quasi-Newton algorithm into the conjugate gradient procedure (this feature is missing in FRCG and PRCG) without increasing storage requirements. We shall present the motivation for the modification and support these arguments by a sample of encouraging computational results.