Prescriptive Analytics: When Data- and Simulation-based Models Interact in a Cooperative Way

Michael Affenzeller, Michael Bogl, Lukas Fischer, Florian Sobieczky, Kaifeng Yang, Jan Zenisek

Publikation: Beitrag in Buch/Bericht/TagungsbandKonferenzbeitragBegutachtung

Abstract

Business analytics is an extensive use of data acquired from diverse sources, statistical and quantitative analysis, explainable and predictive models, and fact-based management to make better strategic decisions for different stakeholders. To be able to model complex systems holistically in such a way that they can be fed into an efficient simulation-based optimization in the sense of prescriptive analytics, approaches and solutions that go beyond state-of-the-art are required. This paper introduces the basic technologies used in prescriptive analytics and proposes secure prescriptive analytics (SPA) that is based on component-based hierarchical modeling and dynamic optimization. Each element under the SPA framework is defined and illustrated by an example of production plan optimization.

OriginalspracheEnglisch
TitelProceedings - 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2022
Redakteure/-innenBruno Buchberger, Mircea Marin, Viorel Negru, Daniela Zaharie
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
Seiten1-8
Seitenumfang8
ISBN (elektronisch)9781665465458
DOIs
PublikationsstatusVeröffentlicht - 2022
Veranstaltung24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2022 - Linz, Österreich
Dauer: 12 Sep. 202215 Sep. 2022

Publikationsreihe

NameProceedings - 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2022

Konferenz

Konferenz24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2022
Land/GebietÖsterreich
OrtLinz
Zeitraum12.09.202215.09.2022

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