Kaname Narukawa

16 papers receiving 494 citations

Hit Papers

A Multiobjective Evolutionary Algorithm Using Gaussian Pr...2015202620182022201550100150200250

Peers

Kaname Narukawa
Comparison fields: 5 of 45
  • Computational Theory and Mathematics 399
  • Artificial Intelligence 390
  • Management Science and Operations Research 80
  • Control and Systems Engineering 59
  • Industrial and Manufacturing Engineering 36
Replace Raquel Hernández Gómez with:
Raquel Hernández Gómez Mexico
Minglei Yin China
Mardé Helbig South Africa
Jingda Deng Hong Kong
Zefeng Chen China
Zhongwei Ma China
Zhenshou Song China
Xuanxuan Ban China
Alan Diaz-Manríquez Mexico
Jiawei Yuan China
Kaname Narukawa relative to Raquel Hernández Gómez Mexico Raquel Hernández Gómez's profile →
Citations per field
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Raquel Hernández Gómez · 1×
Citations per year

Countries citing papers authored by Kaname Narukawa

Since Specialization
Citations

This map shows the geographic impact of Kaname Narukawa's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kaname Narukawa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaname Narukawa more than expected).

Fields of papers citing papers by Kaname Narukawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kaname Narukawa. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kaname Narukawa. The network helps show where Kaname Narukawa may publish in the future.

Co-authorship network of co-authors of Kaname Narukawa

This figure shows the co-authorship network connecting the top 25 collaborators of Kaname Narukawa. A scholar is included among the top collaborators of Kaname Narukawa based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kaname Narukawa. Kaname Narukawa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

17 of 17 papers shown
#WorkIndexed citations
1 16
2
A Multiobjective Evolutionary Algorithm Using Gaussian Process-Based Inverse Modelingbreakdown →
284
3 14
4 10
5 7
6 10
7 3
8 46
9 54
10 10
11
Effects of Similarity-Based Mating Scheme on Evolutionary Function Optimization
4
12 4
13 20
14 2
15 1
16 9
17 12

About Kaname Narukawa

Kaname Narukawa is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Management Science and Operations Research, having authored 17 papers that have together received 506 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (16 papers), Advanced Multi-Objective Optimization Algorithms (16 papers) and Evolutionary Algorithms and Applications (13 papers). The work is most often cited by research in Computational Theory and Mathematics (399 citations), Artificial Intelligence (390 citations) and Management Science and Operations Research (80 citations). Kaname Narukawa has collaborated with scholars based in Japan, Germany and China. Frequent co-authors include Bernhard Sendhoff, Ran Cheng, Yaochu Jin, Hisao Ishibuchi, Yusuke Nojima, Tobias Rodemann, Noritaka Tsukamoto, Yuki Tanigaki, Takahide Yoshiike and Kenta Tanaka. Their work appears in journals such as European Journal of Operational Research, IEEE Transactions on Evolutionary Computation and Soft Computing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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