Machine learning has recently emerged as a prospective area of investigation for OR in general and specifically for combinatorial optimization. Especially after the impressive boost in the effectiveness of deep learning models in various tasks, new approaches, such as neural combinatorial optimization, have been proposed as frameworks to tackle combinatorial optimization problems using a blending of different machine learning techniques. Following this trend, OR conferences and workshops are featuring an ever-increasing number of events and contributions related to the use of machine learning both as an end-to-end heuristic solver and as a component of a solution approach for combinatorial optimization problems.

Di Caro Gianni, M.V. (2021). Machine learning and combinatorial optimization, editorial. OR SPECTRUM, 43(3), 603-605 [10.1007/s00291-021-00642-z].

Machine learning and combinatorial optimization, editorial

Maniezzo Vittorio
;
2021

Abstract

Machine learning has recently emerged as a prospective area of investigation for OR in general and specifically for combinatorial optimization. Especially after the impressive boost in the effectiveness of deep learning models in various tasks, new approaches, such as neural combinatorial optimization, have been proposed as frameworks to tackle combinatorial optimization problems using a blending of different machine learning techniques. Following this trend, OR conferences and workshops are featuring an ever-increasing number of events and contributions related to the use of machine learning both as an end-to-end heuristic solver and as a component of a solution approach for combinatorial optimization problems.
2021
Di Caro Gianni, M.V. (2021). Machine learning and combinatorial optimization, editorial. OR SPECTRUM, 43(3), 603-605 [10.1007/s00291-021-00642-z].
Di Caro Gianni, Maniezzo Vittorio, Montemanni Roberto, Salani Matteo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/828960
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