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Topic · Management Science and Operations Research

Simulation Techniques and Applications

Simulation Techniques and Applications is a research topic within Management Science and Operations Research. Science Explorer counts 28k research works in it since 1950. 14.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the optimization techniques, verification, and validation of simulation models, with an emphasis on agent-based modeling, parallel simulation systems, metamodeling, stochastic approximation, and discrete-event simulation. It also explores the use of sequential procedures in complex adaptive systems and addresses the challenges in modeling and simulation.

  • Simulation Optimization
  • Verification and Validation
  • Agent-Based Modeling
  • Parallel Simulation Systems
  • Metamodeling
  • Stochastic Approximation
  • Discrete-Event Simulation
  • Sequential Procedures
  • Complex Adaptive Systems
  • Modeling and Simulation
Research works
28k
fractional, since 1950
In the world top 10%
3.9k
per year above
Top-10% rate
14.1%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-17%
the tick is no change

Which countries lead Simulation Techniques and Applications research?

By volume, the United States and China publish the most (850 and 470 works in 2022–2025).

By volume, 2022–2025

  1. 1 United States 850 works
  2. 2 China 470 works
  3. 3 Germany 345 works
  4. 4 United Kingdom 161 works
  5. 5 France 154 works
  6. 6 Italy 132 works
  7. 7 India 127 works
  8. 8 Canada 91 works
  9. 9 Russia 90 works
  10. 10 Japan 73 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

United States: 34.1%China: 18.9%Germany: 13.8%United Kingdom: 6.5%6 others listed: 26.7%34%largest
United States850 · 34.1%China470 · 18.9%Germany345 · 13.8%United Kingdom161 · 6.5%6 others listed666 · 26.7%

Shares of the rows listed above, not of the whole node.

Which institutions lead Simulation Techniques and Applications research?

By volume in 2022–2025, Georgia Institute of Technology publishes the most Simulation Techniques and Applications research, followed by RWTH Aachen University and Tsinghua University.

By volume, 2022–2025

  1. 1 Georgia Institute of Technology United States 24 works
  2. 2 RWTH Aachen University Germany 24 works
  3. 3 Tsinghua University China 23 works
  4. 4 Technical University of Munich Germany 15 works
  5. 5 Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) Germany 14 works
  6. 6 Sandia National Laboratories United States 14 works
  7. 7 National University of Defense Technology China 14 works
  8. 8 Beihang University China 14 works
  9. 9 Carnegie Mellon University United States 14 works
  10. 10 University of Stuttgart Germany 14 works

Where is Simulation Techniques and Applications research done?

The largest centres of Simulation Techniques and Applications research in 2022–2025 are Beijing (China), Shanghai (China), London (United Kingdom) and Paris (France). Among places with at least 20 works in it, it is an unusually large share of all research in Stuttgart and Aachen.

Largest cities, 2022–2025

  1. 1 Beijing China 138 works
  2. 2 Shanghai China 50 works
  3. 3 London United Kingdom 47 works
  4. 4 Paris France 40 works
  5. 5 Munich Germany 34 works
  6. 6 Moscow Russia 34 works
  7. 7 Atlanta United States 31 works
  8. 8 Nanjing China 26 works
  9. 9 Xi'an China 26 works
  10. 10 Rome Italy 26 works

Where it is the local speciality

  1. StuttgartDE · 25.5 works8.7×
  2. AachenDE · 25.1 works8.5×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Simulation Techniques and Applications than the world average.

See Simulation Techniques and Applications on the map

Where is the best place to study Simulation Techniques and Applications?

Among universities, judged by research, Georgia Institute of Technology, RWTH Aachen University and Carnegie Mellon University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%10%20%30%mean 17.87%fractional works in this node (log) →share in the world top 10% →Georgia Institute of Technology: 24, 17.0%RWTH Aachen University: 24, 13.7%Carnegie Mellon University: 14, 17.7%University of Stuttgart: 14, 16.1%Peking University: 12, 24.5%Technical University of Munich: 14, 19.4%Tsinghua University: 23, 21.5%Karlsruhe Institute of Technology: 13, 15.0%Cornell University: 12, 19.3%Delft University of Technology: 13, 14.5%Carnegie Mellon Univ…Georgia Institute of…University of Stuttg…RWTH Aachen University
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1Georgia Institute of Technology United States 66.317.0%11.8×24 -18.7%
2RWTH Aachen University Germany 64.413.7%10.2×24 +10.1%
3Carnegie Mellon University United States 59.617.7%10.1×14 +18.4%
4University of Stuttgart Germany 55.716.1%11.7×14 -0.5%
5Peking University China 54.424.5%2.3×12 +223.5%
6Technical University of Munich Germany 52.719.4%5.5×14 +26.8%
7Tsinghua University China 49.721.5%3.4×23 -61.2%
8Karlsruhe Institute of Technology Germany 47.515.0%7.6×13 -32.2%
9Cornell University United States 45.719.3%3.6×12 +86.8%
10Delft University of Technology Netherlands 44.914.5%6.0×13 -18.7%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Simulation Techniques and Applications research growing?

Output in 2018–2022 was 17% lower than in 2013–2017, peaking in 2002.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.