Yu. G. Evtushenko
- Numerical Analysis top 2%
- Computational Theory and Mathematics top 2%
- Control and Systems Engineering top 10%
- Artificial Intelligence
- Computational Mechanics top 10%
- Co-authors
- Mikhail PosypkinV. I. ZubovS. A. LurieLarisa RybakYury SolyaevА. А. ТretyakovA. M. RubinovMichael Khachay
- Topics
- Advanced Optimization Algorithms Research (37 papers)Optimization and Variational Analysis (14 papers)Iterative Methods for Nonlinear Equations (13 papers)
- Journals
- Journal of Optimization Theory and ApplicationsLecture notes in computer scienceJournal of Global Optimization
- Partner nations
- RussiaPolandMontenegro
In The Last Decade
Yu. G. Evtushenko
61 papers receiving 497 citations
Peers
Comparison fields: 5 of 68
- Numerical Analysis 284
- Computational Theory and Mathematics 234
- Control and Systems Engineering 119
- Artificial Intelligence 73
- Computational Mechanics 69
Countries citing papers authored by Yu. G. Evtushenko
This map shows the geographic impact of Yu. G. Evtushenko'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 Yu. G. Evtushenko with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu. G. Evtushenko more than expected).
Fields of papers citing papers by Yu. G. Evtushenko
This network shows the impact of papers produced by Yu. G. Evtushenko. 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 Yu. G. Evtushenko. The network helps show where Yu. G. Evtushenko may publish in the future.
Co-authorship network of co-authors of Yu. G. Evtushenko
This figure shows the co-authorship network connecting the top 25 collaborators of Yu. G. Evtushenko. A scholar is included among the top collaborators of Yu. G. Evtushenko 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 Yu. G. Evtushenko. Yu. G. Evtushenko is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 5 | |
| 4 | 1 | |
| 5 | Numerical method for approximating the solution set of a system of non-linear inequalities | 2 |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 6 | |
| 9 | 26 | |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 1 | |
| 13 | 14 | |
| 14 | 21 | |
| 15 | 7 | |
| 16 | Theorems of the alternative and their applications in numerical methods | 9 |
| 17 | PARETO OPTIMAL NONCOOPERATIVE EQUILIBRIUMS | 0 |
| 18 | A NEW CONCEPT OF THE SOLUTION FOR PROBLEMS OF ACCEPTING OFFERS AND NONCOOPERATIVE GAMES | 0 |
| 19 | 11 | |
| 20 | Integrated Optimization - Simulation System for Industry and Regional Planning. | 0 |
About Yu. G. Evtushenko
Yu. G. Evtushenko is a scholar working on Numerical Analysis, Nuclear Energy and Engineering and Computational Theory and Mathematics, having authored 74 papers that have together received 538 indexed citations. Recurring topics across this work include Advanced Optimization Algorithms Research (37 papers), Optimization and Variational Analysis (14 papers) and Iterative Methods for Nonlinear Equations (13 papers). The work is most often cited by research in Numerical Analysis (284 citations), Computational Theory and Mathematics (234 citations) and Computational Mathematics (8 citations). Yu. G. Evtushenko has collaborated with scholars based in Russia, Poland and Montenegro. Frequent co-authors include Mikhail Posypkin, V. I. Zubov, S. A. Lurie, Larisa Rybak, Yury Solyaev, А. А. Тretyakov, A. M. Rubinov, Michael Khachay, Igor Kaporin and Е. Е. Тыртышников. Their work appears in journals such as Journal of Optimization Theory and Applications, Lecture notes in computer science and Journal of Global Optimization.
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.