Data-driven Optimization
Data-Driven Optimization is an optimization framework that belongs to the class of methods for decision-making under uncertainty and is distinguished by its reliance on empirical data—rather than explicit probabilistic models or assumptions—to directly inform and shape the optimization process.
597
Publications
34K
Citations
2.3K
Authors
757
Institutions
Publications per year
2017–2026
487
597
Peyman Mohajerin Esfahani, Daniel Kühn · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · 2017 · 1.8K citations · Full text
Data-driven robust optimization
Dimitris Bertsimas, Vishal Gupta, Nathan Kallus · Mathematical Programming · 2017 · 594 citations
1–5 of 597
2.3K
Massachusetts Institute of Technology, United States
16 publications · 1.6K citations
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10
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10
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10
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8
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1–5 of 2.3K
757
Massachusetts Institute of Technology
Cambridge, United States
19 h-index
45 publications
3.1K citations

Cornell University
Ithaca, United States
19 h-index
30 publications
3.6K citations
Tsinghua University
Beijing, China
16 h-index
50 publications
2.3K citations
Carnegie Mellon University
Pittsburgh, United States
13 h-index
25 publications
2.7K citations

Shanghai Jiao Tong University
Shanghai, China
12 h-index
28 publications
1K citations
Texas A&M University
College Station, United States
12 h-index
34 publications
1.4K citations
Georgia Institute of Technology
Atlanta, United States
11 h-index
39 publications
1.7K citations
Nanyang Technological University
Singapore, Singapore
11 h-index
20 publications
1.5K citations
1–8 of 757
Repository · 25 publications · 1K citations
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15 publications · 1K citations
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10 publications · 542 citations
10
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11 publications · 585 citations
10
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9 publications · 508 citations
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