2026-07-21T14:13:50Z https://drops.dagstuhl.de/oai

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Data-Driven Combinatorial Optimisation (Dagstuhl Seminar 22431) Frejinger, Emma Lodi, Andrea Lombardi, Michele Yorke-Smith, Neil combinatorial optimisation constraint programming machine learning Mixed integer programming operations research Reinforcement learning Machine learning’s impressive achievements in the last decade have urged many scientific communities to ask if and how the techniques developed in that field to leverage data could be used to advance research in others. The combinatorial optimisation community is one of those, and the area of data-driven combinatorial optimisation has emerged. The motivation of the seminar and its design and development have followed the idea of making researchers both in academia and industry belonging to different communities - from operations research to constraint programming, from artificial intelligence to machine learning - communicate, establish a shared language, and ultimately (try to) set the roadmap for the development of the field. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Emma Frejinger and Andrea Lodi and Michele Lombardi and Neil Yorke-Smith 2023 Is Part Of Dagstuhl Reports, Volume 12, Issue 10 (2023) Article Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagRep.12.10.166 urn:nbn:de:0030-drops-178257 https://drops.dagstuhl.de/entities/document/10.4230/DagRep.12.10.166 eng https://creativecommons.org/licenses/by/4.0/legalcode