Optimization and Search Problems
Optimization and Search Problems is a research topic within Computer Networks and Communications. Science Explorer counts 26k research works in it since 1956. 24.1% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the development and analysis of online algorithms for distributed coordination of mobile robots, with applications in areas such as ad auctions, resource allocation, stochastic matching, and rendezvous search. The research explores techniques for competitive analysis, learning automata, and buffer management in the context of online robotics.
- Online Algorithms
- Mobile Robots
- AdWords Problem
- Resource Allocation
- Stochastic Matching
- Gathering Algorithms
- Learning Automata
- Competitive Analysis
- Rendezvous Search
- Buffer Management
- Research works
- 26k fractional, since 1956
- In the world top 10%
- 6.3k per year above
- Top-10% rate
- 24.1% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +1% the tick is no change
Which countries lead Optimization and Search Problems research?
By volume, China and the United States publish the most (1.1k and 675 works in 2022–2025).
By volume, 2022–2025
- 1 China 1.1k works
- 2 United States 675 works
- 3 India 243 works
- 4 France 175 works
- 5 Germany 157 works
- 6 Japan 131 works
- 7 United Kingdom 125 works
- 8 Canada 119 works
- 9 Italy 101 works
- 10 Israel 87 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 Optimization and Search Problems research?
By volume in 2022–2025, National University of Defense Technology publishes the most Optimization and Search Problems research, followed by Centre National de la Recherche Scientifique and Tsinghua University.
By volume, 2022–2025
- 1 National University of Defense Technology China 27 works
- 2 Centre National de la Recherche Scientifique France 27 works
- 3 Tsinghua University China 23 works
- 4 Shanghai Jiao Tong University China 22 works
- 5 Carnegie Mellon University United States 21 works
- 6 Yunnan University China 21 works
- 7 Harbin Institute of Technology China 21 works
- 8 Beijing Institute of Technology China 21 works
- 9 Georgia Institute of Technology United States 20 works
- 10 Technion – Israel Institute of Technology Israel 19 works
Who are the leading researchers in Optimization and Search Problems?
The most-cited researchers publishing on Optimization and Search Problems include Ion Stoica, Ronald L. Rivest and Philip S. Yu.
- 1 Ion Stoica 9.6k citations
- 2 Ronald L. Rivest 7.3k citations
- 3 Philip S. Yu 6.6k citations
- 4 Wolfram Burgard 6.3k citations
- 5 Zhu Han 4.7k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Optimization and Search Problems research done?
The largest centres of Optimization and Search Problems research in 2022–2025 are Beijing (China), Shanghai (China), Xi'an (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Haifa.
Largest cities, 2022–2025
Where it is the local speciality
- HaifaIL · 24.8 works9.2×
Location quotient: how much more of its research is in Optimization and Search Problems than the world average.
Where is the best place to study Optimization and Search Problems?
Among universities, judged by research, National University of Defense Technology, Shenyang Aerospace University and Yunnan 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.
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 | National University of Defense Technology China | 66.1 | 28.9% | 9.2× | 27 | +71.0% |
| 2 | Shenyang Aerospace University China | 59.8 | 49.7% | 20.4× | 10 | -59.1% |
| 3 | Yunnan University China | 54.2 | 16.2% | 14.8× | 21 | +13.5% |
| 4 | Xidian University China | 52.6 | 48.2% | 4.0× | 11 | +86.8% |
| 5 | Carnegie Mellon University United States | 52.4 | 10.5% | 14.0× | 21 | +20.7% |
| 6 | Space Engineering University China | 52.0 | 33.8% | 32.5× | 9 | — |
| 7 | Massachusetts Institute of Technology United States | 50.9 | 21.5% | 8.2× | 19 | -30.2% |
| 8 | Technion – Israel Institute of Technology Israel | 46.0 | 4.7% | 15.7× | 19 | -11.4% |
| 9 | Columbia University United States | 45.8 | 16.8% | 6.0× | 18 | +64.5% |
| 10 | Indian Statistical Institute India | 44.8 | 15.5% | 29.6× | 9 | +77.1% |
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 Optimization and Search Problems research growing?
Output in 2018–2022 was 1% higher than in 2013–2017, peaking in 2024. The fastest-growing topics are Optimization and Search Problems.
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.