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Topic · Computer Networks and Communications

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. 10.0% 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%
2.6k
per year above
Top-10% rate
10.0%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+11%
the tick is no change
Largest producer
China
39% of the 10 largest, 2022-now
Optimization and Search Problems

Which countries lead Optimization and Search Problems research?

By volume, China and the United States publish the most (1.2k and 741 works in 2022-now).

By volume, 2022-now

  1. 1 China 1.2k works
  2. 2 United States 741 works
  3. 3 India 258 works
  4. 4 France 189 works
  5. 5 Germany 172 works
  6. 6 Japan 140 works
  7. 7 United Kingdom 136 works
  8. 8 Canada 126 works
  9. 9 Italy 105 works
  10. 10 Israel 91 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.

China: 38.7%United States: 23.2%India: 8.1%France: 5.9%6 others listed: 24.1%39%largest
China1,237 · 38.7%United States741 · 23.2%India258 · 8.1%France189 · 5.9%6 others listed770 · 24.1%

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

Which institutions lead Optimization and Search Problems research?

By volume in 2022-now, Centre National de la Recherche Scientifique publishes the most Optimization and Search Problems research, followed by National University of Defense Technology and Chinese Academy of Sciences.

By volume, 2022-now

  1. 1 Centre National de la Recherche ScientifiqueFrance 65 works
  2. 2 National University of Defense TechnologyChina 27 works
  3. 3 Chinese Academy of SciencesChina 27 works
  4. 4 Tsinghua UniversityChina 25 works
  5. 5 Massachusetts Institute of TechnologyUnited States 25 works
  6. 6 Carnegie Mellon UniversityUnited States 24 works
  7. 7 Shanghai Jiao Tong UniversityChina 24 works
  8. 8 Yunnan UniversityChina 22 works
  9. 9 Beijing Institute of TechnologyChina 22 works
  10. 10 Harbin Institute of TechnologyChina 21 works

Who are the leading researchers in Optimization and Search Problems?

The most-cited researchers publishing on Optimization and Search Problems include Yoshua Bengio, Xiaogang Wang and Kai You Wang.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 Xiaogang Wang China 260k citations
  3. 3 Kai You Wang China 224k citations
  4. 4 David H. Haussler United States 209k citations
  5. 5 Bruce Leonard Miller United States 196k citations
  6. 6 Jürgen Schmidhuber Switzerland 188k citations
  7. 7 Michael I. Jordan United States 182k citations
  8. 8 Kalyanmoy Deb United States 171k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Optimization and Search Problems?

The most cited paper in Optimization and Search Problems is "Diagnosing Non-Intermittent Anomalies in Reinforcement Learning Policy Executions (Short Paper)" (Esper, Khalil, Spieck, Jan, Sixdenier, Pierre-Louis et al., 2017), with 11,361 citations. Next come "Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey" (5,863) and "Tabu Search—Part II" (5,669).

Most cited papers
#PaperReleasedCitations
1 Diagnosing Non-Intermittent Anomalies in Reinforcement Learning Policy Executions (Short Paper) Esper, Khalil, Spieck, Jan, Sixdenier, Pierre-Louis et al. · arXiv (Cornell University) PreprintOpen access 20 Jul 2017 11,361
2 Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey Ronald Graham, Eugene L. Lawler, Jan Karel Lenstra et al. · Annals of discrete mathematics Book chapterOpen access 1979 5,863
3 Tabu Search—Part II Fred Glover · INFORMS journal on computing Feb 1990 5,669
4 Tabu Search—Part I Fred Glover · INFORMS journal on computing Aug 1989 5,076
5 Impossibility of distributed consensus with one faulty process Michael J. Fischer, Nancy Ann Lynch, Michael Stewart Paterson · Journal of the ACM Open access Apr 1985 4,607
All 99 most cited papers, with filters and sorting

Where is Optimization and Search Problems research done?

The largest centres of Optimization and Search Problems research in 2022-now 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-now

  1. 1 BeijingChina 211 works
  2. 2 ShanghaiChina 98 works
  3. 3 Xi'anChina 68 works
  4. 4 NanjingChina 64 works
  5. 5 WuhanChina 60 works
  6. 6 ParisFrance 58 works
  7. 7 ChangshaChina 53 works
  8. 8 TokyoJapan 51 works
  9. 9 Hong KongChina 41 works
  10. 10 HangzhouChina 41 works

Where it is the local speciality

  1. HaifaIL · 25.5 works8.8×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Optimization and Search Problems than the world average.

See Optimization and Search Problems on the map

Where is the best place to study Optimization and Search Problems?

Among universities, judged by research, Shenyang Aerospace University, Massachusetts Institute of Technology and National University of Defense 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.

0%20%40%mean 19.53%fractional works in this field (log) →share of work in the world top 10% →Shenyang Aerospace U…Massachusetts Instit…National University …Georgia Institute of…
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Shenyang Aerospace UniversityChina 68.047.5%22.7×11 +131.8%
2Massachusetts Institute of TechnologyUnited States 60.613.7%9.8×25 -9.3%
3National University of Defense TechnologyChina 57.712.9%10.0×27 -2.4%
4Georgia Institute of TechnologyUnited States 57.69.6%9.5×21 +58.7%
5Huazhong University of Science and TechnologyChina 56.724.8%2.8×18 +164.0%
6Beihang UniversityChina 56.521.9%4.7×18 +25.3%
7Tsinghua UniversityChina 55.417.3%3.0×25 +7.1%
8Harbin Institute of TechnologyChina 54.316.7%3.7×21 +85.9%
9Northwestern Polytechnical UniversityChina 54.317.7%4.6×19 +73.9%
10Beijing Institute of TechnologyChina 53.713.2%5.2×22 +114.0%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Optimization and Search Problems, country by country

Is Optimization and Search Problems research growing?

Output in 2022-2025 was 11% higher than in 2018-2021, peaking in 2024. The fastest-growing topics are Optimization and Search Problems.

still counting19801990200020102020
grewheldshrank

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

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Optimization and Search Problems as a percentage of every work published that year, 0.020% in 2024.

still counting0.020%0.040%0.060%Optimization and Search Problems0.018% in 202519801990200020102020

Fractional works of Optimization and Search Problems over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Optimization and Search Problems9.9% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

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.

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