Learning when to use a decomposition
type: Item
instance of: scholarly article
title: Learning when to use a decomposition
zbMATH Open document ID: 1489.68253
DOI: 10.1007/978-3-319-59776-8_16
author: Markus Kruber
author: Marco E. Lübbecke
author: Axel Parmentier
publication date: 2017-08-04T00:00:00Z
Mathematics Subject Classification ID: 68T20
Mathematics Subject Classification ID: 68T05
Mathematics Subject Classification ID: 90C11
zbMATH DE Number: 6756586
zbMATH Keywords: mixed-integer programming
zbMATH Keywords: branch-and-price
zbMATH Keywords: column generation
zbMATH Keywords: automatic Dantzig-Wolfe decomposition
zbMATH Keywords: supervised learning
describes a project that uses: Scikit
describes a project that uses: SCIP
describes a project that uses: MIPLIB
describes a project that uses: GCG
MaRDI profile type: Publication
full work available at URL: 978-3-319-59776-8 16
OpenAlex ID: W2617704759
cites work: SCIP: solving constraint integer programs
cites work: Automatic Dantzig-Wolfe reformulation of mixed integer programs
cites work: 10.1162/15324430260185646
cites work: Random Forests and Adaptive Nearest Neighbors
cites work: A Machine Learning-Based Approximation of Strong Branching
cites work: Q5396710
cites work: Computational Experience with Hypergraph-Based Methods for Automatic Decomposition in Discrete Optimization
description: scientific article; zbMATH DE number 6756586