Tea Tušar
Impact in
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- Advanced Multi-Objective Optimization Algorithms
- Artificial Intelligence top 5%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
Papers in
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- Advanced Multi-Objective Optimization Algorithms 30
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- Metaheuristic Optimization Algorithms Research 20
- Evolutionary Algorithms and Applications 13
- Co-authors
- Bogdan Filipič (29 shared papers)Dimo Brockhoff (8 shared papers)Nikolaus Hansen (6 shared papers)Erik Dovgan (8 shared papers)Matjaž Gams (7 shared papers)Jurij Šilc (1 shared paper)Peter Korošec (1 shared paper)Gregor Papa (1 shared paper)
In The Last Decade
Tea Tušar
46 papers receiving 610 citations
Peers
Comparison fields: 5 of 88
- Computational Theory and Mathematics 306
- Artificial Intelligence 285
- Management Science and Operations Research 85
- Industrial and Manufacturing Engineering 51
- Computer Graphics and Computer-Aided Design 16
Countries citing papers authored by Tea Tušar
This map shows the geographic impact of Tea Tušar'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 Tea Tušar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tea Tušar more than expected).
Fields of papers citing papers by Tea Tušar
This network shows the impact of papers produced by Tea Tušar. 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 Tea Tušar. The network helps show where Tea Tušar may publish in the future.
Co-authors
The 25 scholars most cited alongside Tea Tušar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 175 | |
| 2 | 2014 | 48 | |
| 3 | 2006 | 34 | |
| 4 | 2012 | 30 | |
| 5 | 2019 | 25 | |
| 6 | 2017 | 21 | |
| 7 | 2018 | 21 | |
| 8 | 2019 | 19 | |
| 9 | 2016 | 17 | |
| 10 | 2022 | 16 | |
| 11 | 2022 | 15 | |
| 12 | 2020 | 14 | |
| 13 | 2019 | 14 | |
| 14 | Preliminary Numerical Experiments in Multiobjective Optimization of a Metallurgical Production Process | 2007 | 14 |
| 15 | 2019 | 13 | |
| 16 | 2013 | 12 | |
| 17 | 2011 | 11 | |
| 18 | 2014 | 11 | |
| 19 | 2012 | 11 | |
| 20 | Discovering Comfortable Driving Strategies Using Simulation-Based Multiobjective Optimization | 2012 | 11 |
About Tea Tušar
Tea Tušar is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Control and Systems Engineering, Management Science and Operations Research and Information Systems, having authored 48 papers that have together received 623 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (30 papers), Metaheuristic Optimization Algorithms Research (20 papers), Evolutionary Algorithms and Applications (13 papers), Probabilistic and Robust Engineering Design (5 papers), Advanced Control Systems Optimization (4 papers), Optimal Experimental Design Methods (4 papers), Vehicle emissions and performance (3 papers) and Manufacturing Process and Optimization (3 papers). The work is most often cited by research in Computational Theory and Mathematics (306 citations), Artificial Intelligence (285 citations), Management Science and Operations Research (85 citations), Industrial and Manufacturing Engineering (51 citations) and Computer Graphics and Computer-Aided Design (16 citations). Tea Tušar has collaborated with scholars based in Slovenia, France and Germany. Frequent co-authors include Bogdan Filipič, Dimo Brockhoff, Nikolaus Hansen, Erik Dovgan, Matjaž Gams, Jurij Šilc, Peter Korošec, Gregor Papa, Eric Medvet and Erkki K. Laitinen. Their work appears in journals such as Applied Soft Computing, IEEE Transactions on Evolutionary Computation, Expert Systems with Applications, Genetic Programming and Evolvable Machines and Information Sciences.
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.