Stochastic Programming
Stochastic Programming is a branch of mathematical optimization that extends deterministic programming models by incorporating random parameters into the decision-making process, thereby enabling the formulation of optimal decisions under uncertainty through the minimization of expected costs or risks over multiple scenarios.
6.4K
Publications
460.7K
Citations
10.7K
Authors
2.5K
Institutions
Publications per year
2017–2026
2.1K
6.4K
Adam: A Method for Stochastic Optimization
Diederik P. Kingma, Jimmy Ba · UvA-DARE (University of Amsterdam) · 2014 · 84.8K citations · Full text
Chance-Constrained Programming
A. Charnes, W. W. Cooper · Management Science · 1959 · 2.7K citations
Robust Stochastic Approximation Approach to Stochastic Programming
Arkadi Nemirovski, Anatoli Juditsky, Guanghui Lan et al. · SIAM Journal on Optimization · 2009 · 2.1K citations
1–5 of 6.4K
10.7K
48
h-index
33
h-index
30
h-index
28
h-index
26
h-index
1–5 of 10.7K
2.5K
Georgia Institute of Technology
Atlanta, United States
57 h-index
216 publications
28.7K citations
Massachusetts Institute of Technology
Cambridge, United States
53 h-index
152 publications
16K citations
Tsinghua University
Beijing, China
50 h-index
292 publications
20.2K citations
Carnegie Mellon University
Pittsburgh, United States
48 h-index
192 publications
12.9K citations

University of Regina
Regina, Canada
48 h-index
242 publications
12.9K citations

North China Electric Power University
Beijing, China
45 h-index
300 publications
11.7K citations
University of Michigan
Ann Arbor, United States
40 h-index
167 publications
10.4K citations
Princeton University
Princeton, United States
39 h-index
115 publications
11.9K citations
1–8 of 2.5K
220 publications · 27K citations
96
h-index
212 publications · 24.4K citations
82
h-index
235 publications · 16.4K citations
71
h-index
148 publications · 16.9K citations
68
h-index
65 publications · 8.1K citations
52
h-index
1–5