Exact stochastic constraint optimisation with applications in network analysis

We present an extensive study of methods for exactly solving stochastic constraint (optimisation) problems (SCPs) in network analysis. These problems are prevalent in science, governance and industry. The first method we study is generic and decomposes stochastic constraints into a multitude of smal...

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Veröffentlicht in:	Artificial intelligence Jg. 304; S. 103650
Hauptverfasser:	Latour, Anna L.D., Babaki, Behrouz, Fokkinga, Daniël, Anastacio, Marie, Hoos, Holger H., Nijssen, Siegfried
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.03.2022 Elsevier Science Ltd
Schlagworte:	Algorithms Automated algorithm configuration Configurations Constraint programming Decision theory Decomposition Global constraints Integer programming Linear programming Mixed integer Monotonic probability distributions Network analysis Optimization Ordered binary decision diagrams Probabilistic inference Probabilistic networks Probability theory Solvers Stochastic constraints Ordered binary decision diagrams Global constraints Constraint programming Automated algorithm configuration Probabilistic networks Monotonic probability distributions Probabilistic inference Stochastic constraints
ISSN:	0004-3702, 1872-7921
Online-Zugang:	Volltext
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