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Logarithmic Indicators and the Identification of Subgroups of Variables in Interior-Point Methods.

机译:对数指标与内点法变量子群的识别。

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The identification of certain groups of variables in optimization problems is an important issue and can be used to computational advantage. In this paper new logarithmic indicators are introduced. It is demonstrated that the logarithmic Tapia indicators have superior ability for identifying several subgroups of variables in the context of primal-dual interior-point methods.

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