On handling indicator constraints in mixed integer programming

Mixed integer programming (MIP) is commonly used to model indicator constraints, i.e., constraints that either hold or are relaxed depending on the value of a binary variable. Unfortunately, those models tend to lead to weak continuous relaxations and turn out to be unsolvable in practice; this is w...

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Veröffentlicht in:	Computational optimization and applications Jg. 65; H. 3; S. 545 - 566
Hauptverfasser:	Belotti, Pietro, Bonami, Pierre, Fischetti, Matteo, Lodi, Andrea, Monaci, Michele, Nogales-Gómez, Amaya, Salvagnin, Domenico
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.12.2016 Springer Nature B.V Springer Verlag
Schlagworte:	Algorithms Classification Computation Computer Science Constraint modelling Convex and Discrete Geometry Indicators Integer programming Linear programming Management Science Mathematical analysis Mathematical models Mathematics Mathematics and Statistics Operations Research Operations Research/Decision Theory Optimization Quadratic programming Statistics Studies Support vector machines Tightening Indicator constraints Mixed-integer quadratic programming Mixed-integer linear programming
ISSN:	0926-6003, 1573-2894
Online-Zugang:	Volltext
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