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Machine Learning–Supported Prediction of Dual Variables for the Cutting Stock Problem with an Application in Stabilized Column Generation.

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Title: Machine Learning–Supported Prediction of Dual Variables for the Cutting Stock Problem with an Application in Stabilized Column Generation.
Authors: Kraul, Sebastian1, s.kraul@vu.nl, Seizinger, Markus2, markus.seizinger@uni-a.de, Brunner, Jens O.2,3, jens.brunner@uni-a.de
Source: INFORMS Journal on Computing; May/Jun2023, Vol. 35 Issue 3, p692-709, 18p
Database: Applied Science & Technology Source
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DbLabel: Applied Science & Technology Source
An: 164244303
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PubType: Academic Journal
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  Data: Machine Learning–Supported Prediction of Dual Variables for the Cutting Stock Problem with an Application in Stabilized Column Generation.
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  Data: <searchLink fieldCode="JN" term="%22INFORMS+Journal+on+Computing%22">INFORMS Journal on Computing</searchLink>; May/Jun2023, Vol. 35 Issue 3, p692-709, 18p
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1287/ijoc.2023.1277
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      – Code: eng
        Text: English
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        PageCount: 18
        StartPage: 692
    Titles:
      – TitleFull: Machine Learning–Supported Prediction of Dual Variables for the Cutting Stock Problem with an Application in Stabilized Column Generation.
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            NameFull: Kraul, Sebastian
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            NameFull: Seizinger, Markus
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            NameFull: Brunner, Jens O.
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            – D: 01
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              Text: May/Jun2023
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              Y: 2023
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              Value: 35
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              Value: 3
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            – TitleFull: INFORMS Journal on Computing
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