Ryo Imada

800 total citations
7 papers, 487 citations indexed

About

Ryo Imada is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Ryo Imada has authored 7 papers receiving a total of 487 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computational Theory and Mathematics, 5 papers in Artificial Intelligence and 2 papers in Management Science and Operations Research. Recurrent topics in Ryo Imada's work include Advanced Multi-Objective Optimization Algorithms (7 papers), Evolutionary Algorithms and Applications (5 papers) and Metaheuristic Optimization Algorithms Research (5 papers). Ryo Imada is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (7 papers), Evolutionary Algorithms and Applications (5 papers) and Metaheuristic Optimization Algorithms Research (5 papers). Ryo Imada collaborates with scholars based in Japan and China. Ryo Imada's co-authors include Hisao Ishibuchi, Yusuke Nojima, Yu Setoguchi and Naoki Masuyama and has published in prestigious journals such as IEEE Transactions on Evolutionary Computation, Evolutionary Computation and Proceedings of the Genetic and Evolutionary Computation Conference.

In The Last Decade

Ryo Imada

7 papers receiving 477 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ryo Imada Japan 7 311 265 85 49 44 7 487
Lie Meng Pang China 9 267 0.9× 277 1.0× 69 0.8× 59 1.2× 63 1.4× 46 497
Dhish Kumar Saxena India 10 336 1.1× 296 1.1× 106 1.2× 35 0.7× 60 1.4× 22 465
Shamik Chaudhuri India 6 344 1.1× 250 0.9× 94 1.1× 31 0.6× 62 1.4× 8 501
Qiqi Liu China 14 438 1.4× 443 1.7× 116 1.4× 68 1.4× 58 1.3× 30 779
Hu Zhang China 15 395 1.3× 469 1.8× 46 0.5× 42 0.9× 37 0.8× 46 684
Gregorio Toscano‐Pulido Mexico 14 508 1.6× 428 1.6× 92 1.1× 43 0.9× 57 1.3× 41 718
Yicun Hua China 5 229 0.7× 249 0.9× 47 0.6× 40 0.8× 48 1.1× 8 396
Lucas Bradstreet Australia 10 484 1.6× 388 1.5× 132 1.6× 38 0.8× 50 1.1× 12 573

Countries citing papers authored by Ryo Imada

Since Specialization
Citations

This map shows the geographic impact of Ryo Imada'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 Ryo Imada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryo Imada more than expected).

Fields of papers citing papers by Ryo Imada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryo Imada. 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 Ryo Imada. The network helps show where Ryo Imada may publish in the future.

Co-authorship network of co-authors of Ryo Imada

This figure shows the co-authorship network connecting the top 25 collaborators of Ryo Imada. A scholar is included among the top collaborators of Ryo Imada 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 Ryo Imada. Ryo Imada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

7 of 7 papers shown
1.
Ishibuchi, Hisao, Ryo Imada, Naoki Masuyama, & Yusuke Nojima. (2019). Two-Layered Weight Vector Specification in Decomposition-Based Multi-Objective Algorithms for Many-Objective Optimization Problems. 2434–2441. 6 indexed citations
2.
Ishibuchi, Hisao, Ryo Imada, Yu Setoguchi, & Yusuke Nojima. (2018). Reference Point Specification in Inverted Generational Distance for Triangular Linear Pareto Front. IEEE Transactions on Evolutionary Computation. 22(6). 961–975. 112 indexed citations
3.
Ishibuchi, Hisao, Ryo Imada, Yu Setoguchi, & Yusuke Nojima. (2018). How to Specify a Reference Point in Hypervolume Calculation for Fair Performance Comparison. Evolutionary Computation. 26(3). 411–440. 148 indexed citations
4.
Ishibuchi, Hisao, Ryo Imada, Naoki Masuyama, & Yusuke Nojima. (2018). Dynamic Specification of a Reference Point for Hypervolume Calculation in SMS-EMOA. 1–8. 10 indexed citations
5.
Ishibuchi, Hisao, Ryo Imada, Yu Setoguchi, & Yusuke Nojima. (2017). Reference point specification in hypervolume calculation for fair comparison and efficient search. Proceedings of the Genetic and Evolutionary Computation Conference. 585–592. 70 indexed citations
6.
Ishibuchi, Hisao, Ryo Imada, Yu Setoguchi, & Yusuke Nojima. (2017). Hypervolume Subset Selection for Triangular and Inverted Triangular Pareto Fronts of Three-Objective Problems. 95–110. 12 indexed citations
7.
Ishibuchi, Hisao, Ryo Imada, Yu Setoguchi, & Yusuke Nojima. (2016). Performance comparison of NSGA-II and NSGA-III on various many-objective test problems. 3045–3052. 129 indexed citations

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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