Evolutionary Algorithms and Applications
Evolutionary Algorithms and Applications is a research topic within Artificial Intelligence. Science Explorer counts 31k research works in it since 1951. 22.7% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the application of genetic programming in machine learning, particularly in the areas of classification, feature selection, symbolic regression, and evolvable hardware. It explores the use of evolutionary algorithms and learning classifier systems to solve complex problems, with an emphasis on multiobjective optimization and semantic genetic programming.
- Genetic Programming
- Machine Learning
- Classification
- Evolutionary Algorithms
- Feature Selection
- Symbolic Regression
- Evolvable Hardware
- Learning Classifier Systems
- Semantic Genetic Programming
- Multiobjective Optimization
- Research works
- 31k fractional, since 1951
- In the world top 10%
- 6.9k per year above
- Top-10% rate
- 22.7% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +5% the tick is no change
Which countries lead Evolutionary Algorithms and Applications research?
By volume, China and the United States publish the most (1.1k and 545 works in 2022–2025).
By volume, 2022–2025
- 1 China 1.1k works
- 2 United States 545 works
- 3 India 492 works
- 4 United Kingdom 187 works
- 5 Germany 167 works
- 6 Japan 161 works
- 7 France 116 works
- 8 Mexico 106 works
- 9 Spain 106 works
- 10 Brazil 93 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 Evolutionary Algorithms and Applications research?
By volume in 2022–2025, Victoria University of Wellington publishes the most Evolutionary Algorithms and Applications research, followed by Southern University of Science and Technology and Xidian University.
By volume, 2022–2025
- 1 Victoria University of WellingtonNew Zealand 44 works
- 2 Southern University of Science and TechnologyChina 34 works
- 3 Xidian UniversityChina 26 works
- 4 Michigan State UniversityUnited States 24 works
- 5 South China University of TechnologyChina 20 works
- 6 Northeastern UniversityChina 19 works
- 7 Universidad de GuadalajaraMexico 19 works
- 8 Shenzhen UniversityChina 18 works
- 9 Vellore Institute of Technology UniversityIndia 16 works
- 10 National University of Defense TechnologyChina 15 works
Who are the leading researchers in Evolutionary Algorithms and Applications?
The most-cited researchers publishing on Evolutionary Algorithms and Applications include Yoshua Bengio, Seyedali Mirjalili and Kalyanmoy Deb.
- 1 Yoshua Bengio Canada 17k citations
- 2 Seyedali Mirjalili Australia 7.6k citations
- 3 Kalyanmoy Deb United States 6.7k citations
- 4 Francisco Herrera Spain 6.5k citations
- 5 David Silver United Kingdom 6.1k citations
- 6 Witold Pedrycz Canada 5.4k citations
- 7 Yann LeCun United States 5.4k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Evolutionary Algorithms and Applications research done?
The largest centres of Evolutionary Algorithms and Applications research in 2022–2025 are Beijing (China), Xi'an (China), Shenzhen (China) and Guangzhou (China). Among places with at least 20 works in it, it is an unusually large share of all research in Wellington.
Largest cities, 2022–2025
Where it is the local speciality
- WellingtonNZ · 44.5 works27×
Location quotient: how much more of its research is in Evolutionary Algorithms and Applications than the world average.
Where is the best place to study Evolutionary Algorithms and Applications?
Among universities, judged by research, Victoria University of Wellington, Fujian University of Technology and Southern University of Science and Technology 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.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Victoria University of WellingtonNew Zealand | 68.4 | 28.4% | 48.1× | 44 | +51.9% |
| 2 | Fujian University of TechnologyChina | 65.8 | 61.3% | 24.5× | 11 | — |
| 3 | Southern University of Science and TechnologyChina | 64.4 | 27.2% | 14.0× | 34 | — |
| 4 | Nanjing University of Information Science and TechnologyChina | 64.0 | 46.0% | 7.5× | 14 | +371.7% |
| 5 | Universidad de GuadalajaraMexico | 60.8 | 21.0% | 14.0× | 19 | +232.5% |
| 6 | De Montfort UniversityUnited Kingdom | 60.2 | 51.6% | 21.4× | 9 | +14.0% |
| 7 | Jiangxi University of Water Resources and Electric PowerChina | 58.1 | 52.0% | 25.3× | 8 | +69.8% |
| 8 | Xidian UniversityChina | 55.8 | 40.4% | 7.9× | 26 | -11.2% |
| 9 | University of TriesteItaly | 55.6 | 22.1% | 12.1× | 9 | +578.9% |
| 10 | Shenzhen UniversityChina | 55.4 | 33.5% | 5.4× | 18 | +222.0% |
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 Evolutionary Algorithms and Applications research growing?
Output in 2018–2022 was 5% higher than in 2013–2017, peaking in 2024. The fastest-growing topics are Evolutionary Algorithms and Applications.
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.