Prescriptive Analytics: Optimization and Modeling

Nursah Alkan; Kenan Menguc; Özgür Kabak

doi:10.1007/978-3-030-93823-9_9

Prescriptive Analytics: Optimization and Modeling

Nursah Alkan, Kenan Menguc, Özgür Kabak^*

^*Corresponding author for this work

Department of Industrial Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Prescriptive analytics, a type of complex business analytics, aims to suggest the best among various decision options to benefit from the predicted future using large amounts of data. In this process, prescriptive analytics combines the output of predictive analytics and uses artificial intelligence, optimization algorithms, and expert systems to provide adaptive, automated, constrained, time-bound, and optimal decisions, thus having the potential to bring the greatest intelligence and value to businesses.

Original language	English
Title of host publication	Springer Series in Advanced Manufacturing
Publisher	Springer Nature
Pages	239-264
Number of pages	26
DOIs	https://doi.org/10.1007/978-3-030-93823-9_9
Publication status	Published - 2022

Publication series

Name	Springer Series in Advanced Manufacturing
ISSN (Print)	1860-5168
ISSN (Electronic)	2196-1735

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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10.1007/978-3-030-93823-9_9

Cite this

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Prescriptive Analytics: Optimization and Modeling

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