Data-driven stochastic robust optimization: General computational framework and algorithm leveraging machine learning for optimization under uncertainty in the big data era

•Machine learning based uncertainty model is developed.•A data-driven optimization under uncertainty framework is proposed.•Labeled multi-class uncertainty data is leveraged for decision making.•The resulting problem is solved with a decomposition-based algorithm.•Applications to process network des...

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Veröffentlicht in:	Computers & chemical engineering Jg. 111; S. 115 - 133
Hauptverfasser:	Ning, Chao, You, Fengqi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 04.03.2018
Schlagworte:	Bayesian model Big data Machine learning Optimization under uncertainty Process design and operations Big data Bayesian model Optimization under uncertainty Process design and operations Machine learning
ISSN:	0098-1354, 1873-4375
Online-Zugang:	Volltext
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