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A Machine Learning-Based Approximation of Strong Branching

Alejandro Marcos Alvarez
Corresponding Author
Alejandro Marcos Alvarez
[email protected]
Department of Electrical Engineering and Computer Science, Université de Liège, Sart-Tilman B28, Liège, Belgium
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,
Quentin Louveaux
Quentin Louveaux
[email protected]
Department of Electrical Engineering and Computer Science, Université de Liège, Sart-Tilman B28, Liège, Belgium
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,
Louis Wehenkel
Louis Wehenkel
[email protected]
Department of Electrical Engineering and Computer Science, Université de Liège, Sart-Tilman B28, Liège, Belgium
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Alejandro Marcos Alvarez

Corresponding Author

Alejandro Marcos Alvarez

[email protected]

Department of Electrical Engineering and Computer Science, Université de Liège, Sart-Tilman B28, Liège, Belgium

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Quentin Louveaux

[email protected]

Department of Electrical Engineering and Computer Science, Université de Liège, Sart-Tilman B28, Liège, Belgium

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Louis Wehenkel

[email protected]

Department of Electrical Engineering and Computer Science, Université de Liège, Sart-Tilman B28, Liège, Belgium

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Published Online:13 Jan 2017https://doi.org/10.1287/ijoc.2016.0723

Supplemental Material

ijoc.2016.0723-sm.pdf (145 KB)

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cover image INFORMS Journal on Computing

Volume 29, Issue 1

Winter 2017

Pages 1-195

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Received:September 01, 2014
Accepted:May 01, 2016
Published Online:January 13, 2017

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Alejandro Marcos Alvarez, Quentin Louveaux, Louis Wehenkel (2017) A Machine Learning-Based Approximation of Strong Branching. INFORMS Journal on Computing 29(1):185-195.

https://doi.org/10.1287/ijoc.2016.0723

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A Machine Learning-Based Approximation of Strong Branching

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