Multistage Stochastic Optimization is a mathematical framework for sequential decision-making under uncertainty, distinguished by its modeling of random variables revealed in stages and the adaptive optimization of decisions at each stage to minimize expected costs over time.
396
Publications
21.6K
Citations
904
Authors
435
Institutions
Publications per year
2017–2026
142
Parents
Publications
396
1–5 of 396
Authors
904
- IE
12
h-index
- GH
11
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- LF
11
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8
h-index
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7
h-index
1–5 of 904
Institutions
435
Carnegie Mellon University
Pittsburgh, United States
12 h-index
29 publications
1.8K citations
Georgia Institute of Technology
Atlanta, United States
12 h-index
20 publications
525 citations
Princeton University
Princeton, United States
12 h-index
19 publications
1.8K citations
Universidad Rey Juan Carlos
Madrid, Spain
11 h-index
16 publications
434 citations
University of the Basque Country
Leioa, Spain
10 h-index
26 publications
1K citations
North China Electric Power University
Beijing, China
10 h-index
29 publications
1.7K citations
Tsinghua University
Beijing, China
9 h-index
13 publications
387 citations
Massachusetts Institute of Technology
Cambridge, United States
9 h-index
14 publications
706 citations
1–8 of 435
Venues
- Operations Research
21 publications · 2K citations
20
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- European Journal of Operational Research
24 publications · 932 citations
19
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- INFORMS journal on computing
13 publications · 618 citations
12
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- IEEE Transactions on Power Systems
12 publications · 953 citations
12
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- Mathematical Programming
12 publications · 2K citations
11
h-index
1–5