Scheduling Analytics
Scheduling Analytics is a subfield of operations analytics that applies data-driven quantitative modeling—encompassing descriptive, predictive, and prescriptive methods—to design, evaluate, and optimize the allocation and timing of tasks and resources in scheduling systems under operational constraints and uncertainty.
177
Publications
6.7K
Citations
534
Authors
242
Institutions
Publications per year
2017–2026
81
177
1–5 of 177
534
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3
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1–5 of 534
242
Massachusetts Institute of Technology
Cambridge, United States
9 h-index
13 publications
736 citations

Ghent University
Ghent, Belgium
6 h-index
10 publications
238 citations
Georgia Institute of Technology
Atlanta, United States
5 h-index
7 publications
176 citations

Ames Research Center
Mountain View, United States
4 h-index
4 publications
92 citations
Vlerick Business School
Ghent, Belgium
4 h-index
4 publications
102 citations
University College London
London, United Kingdom
4 h-index
4 publications
102 citations
University of Michigan
Ann Arbor, United States
4 h-index
11 publications
551 citations
University of Iowa
Iowa City, United States
3 h-index
4 publications
253 citations
1–8 of 242
9 publications · 387 citations
9
h-index
6 publications · 168 citations
6
h-index
5 publications · 221 citations
5
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5 publications · 127 citations
5
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4 publications · 256 citations
4
h-index
1–5