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Numerical Research On The Sensitivity Of Nonmonotone Trust Region Algorithms To Their Parameters

机译:非单调信赖域算法对其参数敏感性的数值研究

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In this paper, a numerical research on the sensitivity of nonmonotone trust region algorithms to their parameters is presented. We compare the numerical efficiency of two classes of nonmonotone trust region (NTR) algorithms in the context of unconstrained optimization. We examine the sensitivity of the algorithms to the parameters related to the nonmonotone technique and the initial trust region radius. We show that the numerical efficiency of nonmonotone trust region algorithms can be improved by choosing appropriate parameters. Based on extensive numerical tests, some efficient ranges of these parameters for nonmonotone trust region algorithms are recommended.
机译:本文对非单调信赖域算法对其参数的敏感性进行了数值研究。我们在无约束优化的情况下比较了两类非单调信任区域(NTR)算法的数值效率。我们检查了算法对与非单调技术和初始信任区域半径有关的参数的敏感性。我们表明,通过选择适当的参数可以提高非单调信赖域算法的数值效率。基于大量的数值测试,建议将这些参数的一些有效范围用于非单调信任域算法。

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