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Topic · Computational Theory and Mathematics

Advanced Multi-Objective Optimization Algorithms

Advanced Multi-Objective Optimization Algorithms is a research topic within Computational Theory and Mathematics. Science Explorer counts 32k research works in it since 1951. 9.9% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the application of evolutionary algorithms, surrogate modeling, and optimization techniques to solve multiobjective optimization problems. It covers topics such as genetic algorithms, Pareto fronts, Bayesian optimization, and the use of surrogate models like Kriging for engineering design.

  • Evolutionary Algorithms
  • Multiobjective Optimization
  • Surrogate Modeling
  • Genetic Algorithm
  • Bayesian Optimization
  • Pareto Front
  • Kriging Metamodeling
  • Particle Swarm Optimization
  • Hypervolume Indicator
  • Engineering Design
Research works
32k
fractional, since 1951
In the world top 10%
3.2k
per year above
Top-10% rate
9.9%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+12%
the tick is no change
Largest producer
China
53% of the 10 largest, 2022-now
Advanced Multi-Objective Optimization Algorithms

Which countries lead Advanced Multi-Objective Optimization Algorithms research?

By volume, China and the United States publish the most (3.1k and 820 works in 2022-now).

By volume, 2022-now

  1. 1 China 3.1k works
  2. 2 United States 820 works
  3. 3 India 431 works
  4. 4 Germany 306 works
  5. 5 United Kingdom 286 works
  6. 6 Japan 263 works
  7. 7 France 214 works
  8. 8 Türkiye 157 works
  9. 9 Iran 150 works
  10. 10 South Korea 140 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: 52.9%United States: 14.0%India: 7.3%Germany: 5.2%6 others listed: 20.6%53%largest
China3,104 · 52.9%United States820 · 14.0%India431 · 7.3%Germany306 · 5.2%6 others listed1,211 · 20.6%

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

Which institutions lead Advanced Multi-Objective Optimization Algorithms research?

By volume in 2022-now, Northwestern Polytechnical University publishes the most Advanced Multi-Objective Optimization Algorithms research, followed by Centre National de la Recherche Scientifique and Southern University of Science and Technology.

By volume, 2022-now

  1. 1 Northwestern Polytechnical UniversityChina 77 works
  2. 2 Centre National de la Recherche ScientifiqueFrance 63 works
  3. 3 Southern University of Science and TechnologyChina 58 works
  4. 4 Dalian University of TechnologyChina 55 works
  5. 5 Northeastern UniversityChina 54 works
  6. 6 Xidian UniversityChina 50 works
  7. 7 Huazhong University of Science and TechnologyChina 49 works
  8. 8 Chinese Academy of SciencesChina 45 works
  9. 9 National University of Defense TechnologyChina 42 works
  10. 10 Beihang UniversityChina 40 works

Who are the leading researchers in Advanced Multi-Objective Optimization Algorithms?

The most-cited researchers publishing on Advanced Multi-Objective Optimization Algorithms include Yoshua Bengio, George Davey Smith and Xiaogang Wang.

  1. 1 Yoshua Bengio Canada 476k citations
  2. 2 George Davey Smith United Kingdom 435k citations
  3. 3 Xiaogang Wang China 260k citations
  4. 4 Kai You Wang China 224k 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 Advanced Multi-Objective Optimization Algorithms?

The most cited paper in Advanced Multi-Objective Optimization Algorithms is "A fast and elitist multiobjective genetic algorithm: NSGA-II" (Kalyanmoy Deb, Amrit Pratap, Sakshi Agarwal et al., 2002), with 49,664 citations. Next come "Optimization by Simulated Annealing" (45,251) and "Grey Wolf Optimizer" (19,320).

Most cited papers
#PaperReleasedCitations
1 A fast and elitist multiobjective genetic algorithm: NSGA-II Kalyanmoy Deb, Amrit Pratap, Sakshi Agarwal et al. · IEEE Transactions on Evolutionary Computation Apr 2002 49,664
2 Optimization by Simulated Annealing Scott Kirkpatrick, C. D. Gelatt, Mario P. Vecchi · Science 13 May 1983 45,251
3 Grey Wolf Optimizer Seyedali Mirjalili, Seyed Mohammad Mirjalili, Seyed Mohammad Mirjalili et al. · Advances in Engineering Software Open access 21 Jan 2014 19,320
4 The Whale Optimization Algorithm Seyedali Mirjalili, Andrew W. Lewis · Advances in Engineering Software 26 Feb 2016 14,627
5 A modified particle swarm optimizer Yibing Shi, R.C. Eberhart Conference paper 27 Nov 2002 10,246
All 98 most cited papers, with filters and sorting

Where is Advanced Multi-Objective Optimization Algorithms research done?

The largest centres of Advanced Multi-Objective Optimization Algorithms research in 2022-now are Beijing (China), Xi'an (China), Shanghai (China) and Wuhan (China). Among places with at least 20 works in it, it is an unusually large share of all research in Xiangtan and Palaiseau.

Largest cities, 2022-now

  1. 1 BeijingChina 349 works
  2. 2 Xi'anChina 261 works
  3. 3 ShanghaiChina 188 works
  4. 4 WuhanChina 169 works
  5. 5 NanjingChina 132 works
  6. 6 GuangzhouChina 126 works
  7. 7 ShenzhenChina 124 works
  8. 8 ChangshaChina 114 works
  9. 9 HangzhouChina 91 works
  10. 10 TokyoJapan 91 works

Where it is the local speciality

  1. XiangtanCN · 28.7 works8.0×
  2. PalaiseauFR · 25.3 works7.6×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Advanced Multi-Objective Optimization Algorithms than the world average.

See Advanced Multi-Objective Optimization Algorithms on the map

Where is the best place to study Advanced Multi-Objective Optimization Algorithms?

Among universities, judged by research, Torrens University Australia, Hong Kong Polytechnic University and Fujian University of 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 24.3%fractional works in this field (log) →share of work in the world top 10% →Fujian University of…Torrens University A…Hong Kong Polytechni…Anhui University
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
1Torrens University AustraliaAustralia 68.643.3%54.1×9 +83.7%
2Hong Kong Polytechnic UniversityChina 63.232.6%4.0×23 +158.8%
3Fujian University of TechnologyChina 61.447.4%15.8×10 +35.2%
4Anhui UniversityChina 60.424.0%9.4×29 +167.2%
5Southern University of Science and TechnologyChina 60.211.6%16.0×58 +9.6%
6Northeastern UniversityChina 59.614.7%9.0×54 +68.1%
7Dalian University of TechnologyChina 58.610.9%8.5×55 +21.3%
8Xidian UniversityChina 58.614.9%10.1×50 +22.8%
9China University of GeosciencesChina 56.321.7%10.3×32 +67.8%
10Nanjing University of Information Science and TechnologyChina 54.021.9%8.5×23 +247.4%

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 Advanced Multi-Objective Optimization Algorithms, country by country

Is Advanced Multi-Objective Optimization Algorithms research growing?

Output in 2022-2025 was 12% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Advanced Multi-Objective Optimization Algorithms.

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 Advanced Multi-Objective Optimization Algorithms as a percentage of every work published that year, 0.028% in 2024.

still counting0.020%0.040%Advanced Multi-Objective Optimization Algorithms0.031% in 202519801990200020102020

Fractional works of Advanced Multi-Objective Optimization Algorithms 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%Advanced Multi-Objective Optimization Algorithms9.9% 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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