Anna V. Kononova
- Artificial Intelligence top 5%
- Computational Theory and Mathematics top 5%
- Management Science and Operations Research top 10%
- Electrical and Electronic Engineering
- Computer Networks and Communications
- Co-authors
- Fabio CaraffiniThomas BäckDavid CorneAske PlaatDiederick VermettenVsevolod ShneerPhilippe De WildeBas van Stein
- Topics
- Advanced Multi-Objective Optimization Algorithms (21 papers)Metaheuristic Optimization Algorithms Research (19 papers)Evolutionary Algorithms and Applications (14 papers)
- Cited by
- Computational Theory and MathematicsArtificial IntelligenceManagement Science and Operations Research
- Partner nations
- NetherlandsUnited KingdomGermany
In The Last Decade
Anna V. Kononova
45 papers receiving 486 citations
Peers
Comparison fields: 5 of 97
- Artificial Intelligence 293
- Computational Theory and Mathematics 179
- Management Science and Operations Research 52
- Electrical and Electronic Engineering 44
- Computer Networks and Communications 42
Countries citing papers authored by Anna V. Kononova
This map shows the geographic impact of Anna V. Kononova'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 Anna V. Kononova with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anna V. Kononova more than expected).
Fields of papers citing papers by Anna V. Kononova
This network shows the impact of papers produced by Anna V. Kononova. 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 Anna V. Kononova. The network helps show where Anna V. Kononova may publish in the future.
Co-authorship network of co-authors of Anna V. Kononova
This figure shows the co-authorship network connecting the top 25 collaborators of Anna V. Kononova. A scholar is included among the top collaborators of Anna V. Kononova 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 Anna V. Kononova. Anna V. Kononova is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 4 | |
| 8 | 8 | |
| 9 | 6 | |
| 10 | 28 | |
| 11 | 8 | |
| 12 | 13 | |
| 13 | 2 | |
| 14 | 91 | |
| 15 | 27 | |
| 16 | 2 | |
| 17 | 2 | |
| 18 | 2 | |
| 19 | 1 | |
| 20 | 21 |
About Anna V. Kononova
Anna V. Kononova is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Management Science and Operations Research, having authored 50 papers that have together received 493 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (21 papers), Metaheuristic Optimization Algorithms Research (19 papers) and Evolutionary Algorithms and Applications (14 papers). The work is most often cited by research in Computational Theory and Mathematics (179 citations), Artificial Intelligence (293 citations) and Management Science and Operations Research (52 citations). Anna V. Kononova has collaborated with scholars based in Netherlands, United Kingdom and Germany. Frequent co-authors include Fabio Caraffini, Thomas Bäck, David Corne, Aske Plaat, Diederick Vermetten, Vsevolod Shneer, Philippe De Wilde, Bas van Stein, Hao Wang and Mohamed Pourkashanian. Their work appears in journals such as IEEE Access, Information Sciences and IEEE Transactions on Evolutionary Computation.
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.