The selection of cuts to be added to the current LP relaxation is one of the most critical task in Branch-and-Cut methods, since it strongly affects the performances of the algorithm. Recently, machine learning techniques have become popular to define effective cut selection strategies. In this paper we explore the possibility of selecting cuts by ranking them via support vector regression.

Machine learning techniques for Branch-and-Cut methods: the selection of cutting planes

Marcello Sammarra
Membro del Collaboration Group
;
2023

Abstract

The selection of cuts to be added to the current LP relaxation is one of the most critical task in Branch-and-Cut methods, since it strongly affects the performances of the algorithm. Recently, machine learning techniques have become popular to define effective cut selection strategies. In this paper we explore the possibility of selecting cuts by ranking them via support vector regression.
2023
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
integer linear programs
machine learning
regression
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/461946
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