Bernhard Sendhoff
Impact in
- Computational Theory and Mathematics top 0.02%
- Advanced Multi-Objective Optimization Algorithms
- Artificial Intelligence top 0.1%
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
- Neural Networks and Applications
Papers in
-
- Advanced Multi-Objective Optimization Algorithms 101
-
- Metaheuristic Optimization Algorithms Research 94
- Evolutionary Algorithms and Applications 89
- Neural Networks and Applications 21
- Co-authors
- Yaochu Jin (91 shared papers)Markus Olhofer (35 shared papers)Hans-Georg Beyer (10 shared papers)Ran Cheng (4 shared papers)Yew-Soon Ong (12 shared papers)Tatsuya Okabe (12 shared papers)Dudy Lim (8 shared papers)Xin Yao (44 shared papers)
- Journals
- IEEE Transactions on Evolutionary Computation (12 papers)IEEE Computational Intelligence Magazine (7 papers)Lecture notes in computer science (36 papers)Artificial Life (4 papers)Genetic Programming and Evolvable Machines (3 papers)
- Partner nations
- GermanyJapanUnited Kingdom
In The Last Decade
Bernhard Sendhoff
212 papers receiving 9.9k citations
Bernhard Sendhoff's Hit Papers
Peers
Comparison fields: 5 of 163
- Computational Theory and Mathematics 6.0k
- Artificial Intelligence 5.9k
- Statistics, Probability and Uncertainty 972
- Management Science and Operations Research 1.4k
- Industrial and Manufacturing Engineering 670
Countries citing papers authored by Bernhard Sendhoff
This map shows the geographic impact of Bernhard Sendhoff'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 Bernhard Sendhoff with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernhard Sendhoff more than expected).
Fields of papers citing papers by Bernhard Sendhoff
This network shows the impact of papers produced by Bernhard Sendhoff. 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 Bernhard Sendhoff. The network helps show where Bernhard Sendhoff may publish in the future.
Co-authors
The 25 scholars most cited alongside Bernhard Sendhoff, 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 215 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization Hit paper breakdown → | 2016 | 1384 |
| 2 | Robust optimization – A comprehensive survey Hit paper breakdown → | 2007 | 1257 |
| 3 | A framework for evolutionary optimization with approximate fitness functions Hit paper breakdown → | 2002 | 561 |
| 4 | Generalizing Surrogate-Assisted Evolutionary Computation Hit paper breakdown → | 2009 | 409 |
| 5 | Pareto-Based Multiobjective Machine Learning: An Overview and Case Studies Hit paper breakdown → | 2008 | 371 |
| 6 | Test Problems for Large-Scale Multiobjective and Many-Objective Optimization Hit paper breakdown → | 2016 | 334 |
| 7 | A Multiobjective Evolutionary Algorithm Using Gaussian Process-Based Inverse Modeling Hit paper breakdown → | 2015 | 318 |
| 8 | 2006 | 251 | |
| 9 | 2004 | 225 | |
| 10 | 2007 | 192 | |
| 11 | 2005 | 167 | |
| 12 | 2003 | 166 | |
| 13 | 2004 | 165 | |
| 14 | 1999 | 162 | |
| 15 | 2006 | 161 | |
| 16 | 2009 | 158 | |
| 17 | Dynamic Weighted Aggregation for Evolutionary Multi-Objective Optimization: Why Does It Work and How? | 2007 | 143 |
| 18 | On Evolutionary Optimization with Approximate Fitness Functions. | 2000 | 129 |
| 19 | 2004 | 119 | |
| 20 | 2007 | 109 |
About Bernhard Sendhoff
Bernhard Sendhoff is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Computational Mechanics, Industrial and Manufacturing Engineering and Computer Graphics and Computer-Aided Design, having authored 215 papers that have together received 10.2k indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (101 papers), Metaheuristic Optimization Algorithms Research (94 papers), Evolutionary Algorithms and Applications (89 papers), Neural Networks and Applications (21 papers), 3D Shape Modeling and Analysis (15 papers), Gene Regulatory Network Analysis (15 papers), Evolution and Genetic Dynamics (14 papers) and Turbomachinery Performance and Optimization (13 papers). The work is most often cited by research in Computational Theory and Mathematics (6.0k citations), Artificial Intelligence (5.9k citations), Statistics, Probability and Uncertainty (972 citations), Management Science and Operations Research (1.4k citations) and Industrial and Manufacturing Engineering (670 citations). Bernhard Sendhoff has collaborated with scholars based in Germany, Japan and United Kingdom. Frequent co-authors include Yaochu Jin, Markus Olhofer, Hans-Georg Beyer, Ran Cheng, Yew-Soon Ong, Tatsuya Okabe, Dudy Lim, Xin Yao, Qingfu Zhang and Aimin Zhou. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, IEEE Computational Intelligence Magazine, Lecture notes in computer science, Artificial Life and Genetic Programming and Evolvable Machines.
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.