Modeling, Simulation, and Optimization
Modeling, Simulation, and Optimization is a research topic within Discrete Mathematics and Combinatorics. Science Explorer counts 6.2k research works in it since 1950. 8.6% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the application of fuzzy fractal dimensions and modeling techniques in granular data, particularly in the context of fuzzy clustering, probabilistic topic models, information granularity, ontology-based simulations, agent-based modeling, and simulation optimization hybrids. The papers explore the use of evolutionary algorithms and control frameworks to address complex problems in various domains.
- Fuzzy Fractal Dimensions
- Granular Data
- Fuzzy Clustering
- Probabilistic Topic Models
- Information Granularity
- Ontology-Based Simulations
- Agent-Based Modeling
- Simulation Optimization Hybrids
- Evolutionary Algorithms
- Control Framework
- Research works
- 6.2k fractional, since 1950
- In the world top 10%
- 538 per year above
- Top-10% rate
- 8.6% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- -9% the tick is no change
Which countries lead Modeling, Simulation, and Optimization research?
By volume, Russia and China publish the most (125 and 97 works in 2022–2025).
By volume, 2022–2025
- 1 Russia 125 works
- 2 China 97 works
- 3 United States 76 works
- 4 India 44 works
- 5 Germany 42 works
- 6 Ukraine 40 works
- 7 Indonesia 33 works
- 8 Poland 24 works
- 9 United Kingdom 22 works
- 10 Italy 22 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.
Shares of the rows listed above, not of the whole node.
Which institutions lead Modeling, Simulation, and Optimization research?
By volume in 2022–2025, Voronezh State University of Forestry and Technologies publishes the most Modeling, Simulation, and Optimization research, followed by Bauman Moscow State Technical University and V. A. Trapeznikov Institute of Control Sciences.
By volume, 2022–2025
- 1 Voronezh State University of Forestry and Technologies Russia 6 works
- 2 Bauman Moscow State Technical University Russia 4 works
- 3 V. A. Trapeznikov Institute of Control Sciences Russia 4 works
- 4 Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) Germany 4 works
- 5 National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Ukraine 3 works
- 6 Moscow Aviation Institute Russia 3 works
- 7 St Petersburg University Russia 3 works
- 8 Rostov State Transport University Russia 3 works
- 9 Alberta Bible College Canada 3 works
- 10 Delft University of Technology Netherlands 3 works
Who are the leading researchers in Modeling, Simulation, and Optimization?
The most-cited researchers publishing on Modeling, Simulation, and Optimization include Witold Pedrycz.
- 1 Witold Pedrycz 5.4k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Modeling, Simulation, and Optimization research done?
The largest centres of Modeling, Simulation, and Optimization research in 2022–2025 are Moscow (Russia), Beijing (China), Saint Petersburg (Russia) and Kyiv (Ukraine). Among places with at least 20 works in it, it is an unusually large share of all research in Moscow and Beijing.
Largest cities, 2022–2025
Where it is the local speciality
- MoscowRU · 39.6 works4.7×
- BeijingCN · 20.2 works0.7×
Location quotient: how much more of its research is in Modeling, Simulation, and Optimization than the world average.
Is Modeling, Simulation, and Optimization research growing?
Output in 2018–2022 was 9% lower than in 2013–2017, peaking in 2024. The fastest-growing topics are Modeling, Simulation, and Optimization.
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.