Simulation-Based Stochastic Optimization is a methodological framework within stochastic optimization that employs simulation to estimate objective functions and constraints under uncertainty, distinguishing itself by iteratively refining solutions using noisy, simulation-generated data rather than explicit analytical models.
508
Publications
25.7K
Citations
1K
Authors
482
Institutions
Publications per year
2017–2026
152
Publications
508
1–5 of 508
Authors
1K
- LH
15
h-index
- CC
13
h-index
- BL
11
h-index
- PW
10
h-index
- MC
10
h-index
1–5 of 1K
Institutions
482
Georgia Institute of Technology
Atlanta, United States
17 h-index
34 publications
5.6K citations
National University of Singapore
Singapore, Singapore
17 h-index
41 publications
1.7K citations
George Mason University
Fairfax, United States
16 h-index
29 publications
1.6K citations
University of Wisconsin–Madison
Madison, United States
14 h-index
22 publications
1.6K citations
University of Maryland, College Park
College Park, United States
12 h-index
23 publications
1.2K citations
Northwestern University
Evanston, United States
11 h-index
26 publications
1.3K citations
Purdue University West Lafayette
West Lafayette, United States
10 h-index
19 publications
927 citations
Cornell University
Ithaca, United States
10 h-index
18 publications
750 citations
1–8 of 482
Venues
- European Journal of Operational Research
18 publications · 631 citations
17
h-index
- Operations Research
15 publications · 1.4K citations
15
h-index
- IIE Transactions
13 publications · 695 citations
13
h-index
- Winter Simulation Conference
Conference · 14 publications · 423 citations
12
h-index
- Computers & Chemical Engineering
8 publications · 431 citations
9
h-index
1–5