Data-Driven Optimization under Uncertainty in the Era of Big Data and Deep Learning: General Frameworks, Algorithms, and Applications

This dissertation deals with the development of fundamental data-driven optimization under uncertainty, including its modeling frameworks, solution algorithms, and a wide variety of applications. Specifically, three research aims are proposed, including data-driven distributionally robust optimizati...

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Bibliographic Details
Main Author:	Ning, Chao
Format:	Dissertation
Language:	English
Published:	ProQuest Dissertations & Theses 01.01.2020
Subjects:	Artificial intelligence Information science Systems science
ISBN:	9798672146201
Online Access:	Get full text
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