Benjamin Doerr

946 citations
33 papers · 499 · h-index 14

Impact in

    • Advanced Multi-Objective Optimization Algorithms
    • Metaheuristic Optimization Algorithms Research
    • Evolutionary Algorithms and Applications
    • Algorithms and Data Compression
    • Reinforcement Learning in Robotics
    • Machine Learning and Algorithms

Papers in

    • Evolutionary Algorithms and Applications 23
    • Metaheuristic Optimization Algorithms Research 22
    • Algorithms and Data Compression 5
    • Artificial Intelligence in Games 3
    • Reinforcement Learning in Robotics 3
    • Machine Learning and Algorithms 2
    • Bayesian Modeling and Causal Inference 2
    • Advanced Multi-Objective Optimization Algorithms 12

Benjamin Doerr

32 papers receiving 494 citations

Peers

Benjamin Doerr
Comparison fields: 5 of 61
  • Computational Theory and Mathematics 276
  • Artificial Intelligence 413
  • Industrial and Manufacturing Engineering 34
  • Computer Networks and Communications 67
  • Management Science and Operations Research 31
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Cláudio N. Meneses Brazil
Nils Hebbinghaus Germany
Franco Mascia Italy
Franz Oppacher Canada
Javier G. Marı́n-Blázquez Spain
Shuangbao Song Japan
Alexey Ignatiev Australia
Ewald Speckenmeyer Germany
Andrei Lissovoi United Kingdom
Luís M. S.​Russo Portugal
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Citations per field
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Citations per year

Countries citing papers authored by Benjamin Doerr

Since Specialization
Citations

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

Fields of papers citing papers by Benjamin Doerr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Benjamin Doerr, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Benjamin Doerr Line = papers co-authored together Benjamin Doerr links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201998
2 201135
3 201031
4 201830
5 201730
6 200729
7 202326
8 201022
9 201920
10 201920
11 201618
12 201816
13 201916
14 201315
15 201713
16 202212
17 202010
18 20188
19 20207
20
Memory-Constrained Algorithms for Shortest Path Problem
20116

About Benjamin Doerr

Benjamin Doerr is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology, Signal Processing and Management Science and Operations Research, having authored 33 papers that have together received 499 indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (23 papers), Metaheuristic Optimization Algorithms Research (22 papers), Advanced Multi-Objective Optimization Algorithms (12 papers), Algorithms and Data Compression (5 papers), Artificial Intelligence in Games (3 papers), Reinforcement Learning in Robotics (3 papers), Machine Learning and Algorithms (2 papers) and Bayesian Modeling and Causal Inference (2 papers). The work is most often cited by research in Computational Theory and Mathematics (276 citations), Artificial Intelligence (413 citations), Industrial and Manufacturing Engineering (34 citations), Computer Networks and Communications (67 citations) and Management Science and Operations Research (31 citations). Benjamin Doerr has collaborated with scholars based in France, Germany and Denmark. Frequent co-authors include Carsten Witt, Frank Neumann, Mahmoud Fouz, Jing Yang, Dirk Sudholt, Zhongdi Qu, Andrew M. Sutton, Denis Antipov, Timo Kötzing and Martin S. Krejca. Their work appears in journals such as Algorithmica, Theoretical Computer Science, Soft Computing, Artificial Intelligence and Proceedings of the Genetic and Evolutionary Computation Conference Companion.

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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