Multi-task Representation Learning for Mixed Integer Linear Programming
Multi-task Representation Learning for Mixed Integer Linear Programming
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Contents
Mixed Integer Linear Programs (MILPs) are highly flexible and powerful tools for modeling and solving complex real-world combinatorial optimization problems. Recently, machine learning (ML)-guided approaches have demonstrated significant potential in improving MILP-solving efficiency. However, these methods typically rely on separate offline data c...
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Multi-task Representation Learning for Mixed Integer Linear Programming
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TN_cdi_proquest_journals_3147563747
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_3147563747
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E-ISSN
2331-8422
