Benjamin Doerr

926 citations
33 papers · 487 indexed · h-index 14

Benjamin Doerr

32 papers receiving 482 citations

Peers

Benjamin Doerr
Comparison fields: 5 of 60
  • Computational Theory and Mathematics 274
  • Artificial Intelligence 405
  • Industrial and Manufacturing Engineering 31
  • Computer Networks and Communications 62
  • Management Science and Operations Research 31
Replace Javier G. Marı́n-Blázquez with:
Javier G. Marı́n-Blázquez Spain
Cláudio N. Meneses Brazil
Franco Mascia Italy
Nils Hebbinghaus Germany
Andrei Lissovoi United Kingdom
Shuangbao Song Japan
Luís M. S.​Russo Portugal
Shui-Li Chen China
Jing-Cheng Shi China
Jiřı́ Kubalı́k Czechia
Benjamin Doerr relative to Javier G. Marı́n-Blázquez Spain Javier G. Marı́n-Blázquez's profile →
Citations per field
00.5×10×15×19.3×
Javier G. Marı́n-Blázquez · 1×
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-authorship network

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
#Work
1 20251
2 20232
3 20231
4 20232
5 20231
6 20235
7 202326
8 20231
9 202010
10 20207
11 20195
12 201995
13 201920
14 201919
15 20180
16 201815
17
Memory-Constrained Algorithms for Shortest Path Problem
20116
18 201135
19 201031
20 200728

About Benjamin Doerr

Benjamin Doerr is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Graphics and Computer-Aided Design, having authored 33 papers that have together received 487 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), Reinforcement Learning in Robotics (3 papers), Artificial Intelligence in Games (3 papers), Bayesian Modeling and Causal Inference (2 papers) and Machine Learning and Algorithms (2 papers). The work is most often cited by research in Computational Theory and Mathematics (274 citations), Artificial Intelligence (405 citations) and Industrial and Manufacturing Engineering (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, Denis Antipov, Andrew M. Sutton, Timo Kötzing and Johannes Lengler. Their work appears in journals such as Theoretical Computer Science, Algorithmica, Artificial Intelligence, Soft Computing and SPIRE - Sciences Po Institutional REpository.

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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