@inproceedings{180fad94b9ed45908320acc30fa1a752,
title = "Prescriptive Analytics: When Data- and Simulation-based Models Interact in a Cooperative Way",
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.",
keywords = "Business Analytics, Information Security, Optimization, Prescriptive Analytics, Secure Prescriptive Analytics, Simulation, Surrogate Models",
author = "Michael Affenzeller and Michael Bogl and Lukas Fischer and Florian Sobieczky and Kaifeng Yang and Jan Zenisek",
note = "Funding Information: This project is financed by research subsidies granted by the government of Upper Austria. Publisher Copyright: {\textcopyright} 2022 IEEE.; 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2022 ; Conference date: 12-09-2022 Through 15-09-2022",
year = "2022",
doi = "10.1109/SYNASC57785.2022.00009",
language = "English",
series = "Proceedings - 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--8",
editor = "Bruno Buchberger and Mircea Marin and Viorel Negru and Daniela Zaharie",
booktitle = "Proceedings - 2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2022",
address = "United States",
}