Scheduling and Optimization Algorithms
Scheduling and Optimization Algorithms is a research topic within Industrial and Manufacturing Engineering. Science Explorer counts 42k research works in it since 1950. 23.3% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on scheduling problems in manufacturing systems, particularly addressing issues such as setup times, batching, dynamic scheduling, energy efficiency, and multi-objective optimization. It explores various techniques including genetic algorithms, agent-based control, and hybrid optimization to improve scheduling efficiency and effectiveness in manufacturing processes.
- Scheduling
- Manufacturing
- Flexible Job-shop
- Genetic Algorithm
- Agent-based Control
- Energy-efficient
- Hybrid Optimization
- Flowshop Sequencing
- Dynamic Scheduling
- Multi-objective
- Research works
- 42k fractional, since 1950
- In the world top 10%
- 9.7k per year above
- Top-10% rate
- 23.3% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +1% the tick is no change
Which countries lead Scheduling and Optimization Algorithms research?
By volume, China and the United States publish the most (1.9k and 542 works in 2022–2025).
By volume, 2022–2025
- 1 China 1.9k works
- 2 United States 542 works
- 3 India 416 works
- 4 Germany 381 works
- 5 France 278 works
- 6 Indonesia 203 works
- 7 United Kingdom 141 works
- 8 Türkiye 135 works
- 9 Italy 131 works
- 10 Brazil 121 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 Scheduling and Optimization Algorithms research?
By volume in 2022–2025, Huazhong University of Science and Technology publishes the most Scheduling and Optimization Algorithms research, followed by Wuhan University of Technology and Northeastern University.
By volume, 2022–2025
- 1 Huazhong University of Science and Technology China 71 works
- 2 Wuhan University of Technology China 51 works
- 3 Northeastern University China 41 works
- 4 Tsinghua University China 36 works
- 5 Tongji University China 35 works
- 6 Liaocheng University China 33 works
- 7 Shanghai University China 32 works
- 8 Shanghai Jiao Tong University China 32 works
- 9 Beijing Institute of Technology China 29 works
- 10 Centre National de la Recherche Scientifique France 27 works
Who are the leading researchers in Scheduling and Optimization Algorithms?
The most-cited researchers publishing on Scheduling and Optimization Algorithms include Wil M. P. van der Aalst, Luca Benini and Marco Dorigo.
- 1 Wil M. P. van der Aalst 5.5k citations
- 2 Luca Benini 4.6k citations
- 3 Marco Dorigo 4.5k citations
- 4 MengChu Zhou 4.4k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Scheduling and Optimization Algorithms research done?
The largest centres of Scheduling and Optimization Algorithms research in 2022–2025 are Beijing (China), Wuhan (China), Shanghai (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Liaocheng.
Largest cities, 2022–2025
Where it is the local speciality
- LiaochengCN · 33.1 works26×
Location quotient: how much more of its research is in Scheduling and Optimization Algorithms than the world average.
Where is the best place to study Scheduling and Optimization Algorithms?
Among universities, judged by research, Macau University of Science and Technology, Victoria University of Wellington and Huazhong 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 | Macau University of Science and Technology Macau | 72.9 | 46.5% | 14.6× | 19 | +93.8% |
| 2 | Victoria University of Wellington New Zealand | 69.8 | 46.3% | 10.9× | 14 | +181.5% |
| 3 | Huazhong University of Science and Technology China | 64.1 | 48.1% | 7.3× | 72 | -4.8% |
| 4 | Liaocheng University China | 62.1 | 50.3% | 30.1× | 33 | -71.4% |
| 5 | Wuhan University of Science and Technology China | 61.3 | 49.3% | 8.8× | 18 | +92.0% |
| 6 | Wuhan University of Technology China | 59.9 | 27.4% | 10.1× | 50 | +19.6% |
| 7 | China University of Geosciences China | 56.0 | 65.9% | 5.6× | 16 | +11.3% |
| 8 | Shenyang Aerospace University China | 54.3 | 51.4% | 16.9× | 14 | -61.1% |
| 9 | Eindhoven University of Technology Netherlands | 51.1 | 33.6% | 8.5× | 19 | -23.1% |
| 10 | Shanghai University China | 49.9 | 31.1% | 7.2× | 32 | +9.1% |
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 Scheduling and Optimization Algorithms research growing?
Output in 2018–2022 was 1% higher than in 2013–2017, peaking in 2024. The fastest-growing topics are Scheduling and Optimization Algorithms.
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.