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A note on the global convergence theorem of the scaled conjugate gradient algorithms proposed by Andrei

机译:关于Andrei提出的比例共轭梯度算法的全局收敛定理的注记

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In (Andrei, Comput. Optim. Appl. 38:402-416, 2007), the efficient scaled conjugate gradient algorithm SCALCG is proposed for solving unconstrained optimization problems. However, due to a wrong inequality used in (Andrei, Comput. Optim. Appl. 38:402-416, 2007) to show the sufficient descent property for the search directions of SCALCG, the proof of Theorem 2, the global convergence theorem of SCALCG, is incorrect. Here, in order to complete the proof of Theorem 2 in (Andrei, Comput. Optim. Appl. 38:402-416, 2007), we show that the search directions of SCALCG satisfy the sufficient descent condition. It is remarkable that the convergence analyses in (Andrei, Optim. Methods Softw. 22:561-571, 2007; Eur. J. Oper. Res. 204:410-420, 2010) should be revised similarly.
机译:在(Andrei,Comput.Optim.Appl.38:402-416,2007)中,提出了有效的按比例缩放的共轭梯度算法SCALCG来解决无约束的优化问题。但是,由于在(Andrei,Comput。Optim。Appl。38:402-416,2007)中使用了错误的不等式来显示SCALCG的搜索方向具有足够的下降性质,因此定理2的证明,定理2的全局收敛定理SCALCG,不正确。在此,为了完成定理2的证明(Andrei,计算机最优化应用程序38:402-416,2007),我们证明SCALCG的搜索方向满足足够的下降条件。值得注意的是(Andrei,Optim。Methods Softw。22:561-571,2007; Eur。J. Oper。Res.204:410-420,2010)中的收敛性分析也应进行类似的修订。

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