Benjamin Doerr

6.1k total citations
149 papers, 2.4k citations indexed

About

Benjamin Doerr is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Benjamin Doerr has authored 149 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 101 papers in Artificial Intelligence, 81 papers in Computational Theory and Mathematics and 23 papers in Computer Networks and Communications. Recurrent topics in Benjamin Doerr's work include Metaheuristic Optimization Algorithms Research (79 papers), Evolutionary Algorithms and Applications (66 papers) and Advanced Multi-Objective Optimization Algorithms (61 papers). Benjamin Doerr is often cited by papers focused on Metaheuristic Optimization Algorithms Research (79 papers), Evolutionary Algorithms and Applications (66 papers) and Advanced Multi-Objective Optimization Algorithms (61 papers). Benjamin Doerr collaborates with scholars based in France, Germany and China. Benjamin Doerr's co-authors include Weijie Zheng, Carola Doerr, Anne Auger, Tobias Friedrich, Mahmoud Fouz, Frank Neumann, Timo Kötzing, Denis Antipov, Maxim Buzdalov and Christian Klein and has published in prestigious journals such as Communications of the ACM, Artificial Intelligence and IEEE Transactions on Evolutionary Computation.

In The Last Decade

Benjamin Doerr

137 papers receiving 2.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Benjamin Doerr France 26 1.6k 1.2k 273 228 130 149 2.4k
Tobias Friedrich Germany 25 1.2k 0.8× 1.1k 0.9× 354 1.3× 362 1.6× 129 1.0× 176 2.3k
Wenjian Luo China 20 1.4k 0.9× 763 0.6× 234 0.9× 267 1.2× 73 0.6× 160 2.0k
Carola Doerr France 21 1.1k 0.7× 721 0.6× 205 0.8× 81 0.4× 112 0.9× 145 1.4k
Jun He China 26 1.4k 0.9× 913 0.8× 287 1.1× 38 0.2× 174 1.3× 110 2.2k
Sergiy Butenko United States 24 431 0.3× 713 0.6× 448 1.6× 626 2.7× 209 1.6× 85 2.1k
Carsten Witt Denmark 30 2.2k 1.3× 1.3k 1.1× 360 1.3× 45 0.2× 287 2.2× 109 2.6k
Alessandro Panconesi Italy 29 978 0.6× 996 0.8× 1.6k 5.7× 556 2.4× 62 0.5× 99 3.0k
D. Long United States 8 1.8k 1.1× 2.7k 2.2× 570 2.1× 31 0.1× 76 0.6× 12 4.3k
Hisao Tamaki Japan 16 880 0.5× 472 0.4× 307 1.1× 138 0.6× 53 0.4× 62 1.8k
Jianshe Wu China 22 818 0.5× 677 0.6× 509 1.9× 575 2.5× 55 0.4× 75 1.7k

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 of co-authors of Benjamin Doerr

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin Doerr. A scholar is included among the top collaborators of Benjamin Doerr 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 Benjamin Doerr. Benjamin Doerr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Doerr, Benjamin, et al.. (2025). Hot off the Press: Speeding Up the NSGA-II With a Simple Tie-Breaking Rule. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 25–26.
2.
Doerr, Benjamin, et al.. (2025). Difficulties of the NSGA-II With the Many-Objective LeadingOnes Problem. IEEE Transactions on Evolutionary Computation. 1–1. 2 indexed citations
3.
Doerr, Benjamin, et al.. (2024). Superior Genetic Algorithms for the Target Set Selection Problem Based on Power-Law Parameter Choices and Simple Greedy Heuristics. Proceedings of the Genetic and Evolutionary Computation Conference. 169–177. 1 indexed citations
4.
Zheng, Weijie & Benjamin Doerr. (2024). Hot off the Press: Runtime Analysis of the SMS-EMOA for Many-Objective Optimization. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 69–70. 1 indexed citations
5.
Doerr, Benjamin. (2024). A Gentle Introduction to Theory (for Non-Theoreticians). Proceedings of the Genetic and Evolutionary Computation Conference Companion. 800–829.
6.
Antipov, Denis, Maxim Buzdalov, & Benjamin Doerr. (2024). First Steps Toward a Runtime Analysis When Starting With a Good Solution. arXiv (Cornell University). 5(2). 1–41. 1 indexed citations
7.
Zheng, Weijie & Benjamin Doerr. (2024). Hot off the Press: Runtime Analysis for the NSGA-II: Proving, Quantifying, and Explaining the Inefficiency For Many Objectives. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 67–68. 1 indexed citations
8.
Antipov, Denis, et al.. (2024). Already Moderate Population Sizes Provably Yield Strong Robustness to Noise. Proceedings of the Genetic and Evolutionary Computation Conference. 1524–1532. 2 indexed citations
9.
Doerr, Benjamin, et al.. (2024). A Mathematical Runtime Analysis of the Non-dominated Sorting Genetic Algorithm III (NSGA-III). Proceedings of the Genetic and Evolutionary Computation Conference Companion. 63–64. 4 indexed citations
10.
Doerr, Benjamin, Joshua Knowles, Aneta Neumann, & Frank Neumann. (2024). A Block-Coordinate Descent EMO Algorithm: Theoretical and Empirical Analysis. Proceedings of the Genetic and Evolutionary Computation Conference. 493–501. 1 indexed citations
11.
Zheng, Weijie & Benjamin Doerr. (2024). Approximation Guarantees for the Nondominated Sorting Genetic Algorithm II (NSGA-II). IEEE Transactions on Evolutionary Computation. 29(4). 891–905. 6 indexed citations
12.
Zheng, Weijie & Benjamin Doerr. (2023). Runtime Analysis for the NSGA-II: Proving, Quantifying, and Explaining the Inefficiency for Many Objectives. IEEE Transactions on Evolutionary Computation. 28(5). 1442–1454. 23 indexed citations
13.
Zheng, Weijie & Benjamin Doerr. (2023). Mathematical runtime analysis for the non-dominated sorting genetic algorithm II (NSGA-II). Artificial Intelligence. 325. 104016–104016. 40 indexed citations
14.
Antipov, Denis, Maxim Buzdalov, & Benjamin Doerr. (2022). Fast Mutation in Crossover-Based Algorithms. Algorithmica. 84(6). 1724–1761. 19 indexed citations
15.
Antipov, Denis, et al.. (2022). A Rigorous Runtime Analysis of the $$(1 + (\lambda , \lambda ))$$ GA on Jump Functions. Algorithmica. 84(6). 1573–1602. 10 indexed citations
16.
Doerr, Benjamin & Weijie Zheng. (2020). Sharp Bounds for Genetic Drift in Estimation of Distribution Algorithms. IEEE Transactions on Evolutionary Computation. 24(6). 1140–1149. 30 indexed citations
17.
Afshani, Peyman, Manindra Agrawal, Benjamin Doerr, et al.. (2019). The query complexity of a permutation-based variant of Mastermind. Discrete Applied Mathematics. 260. 28–50. 9 indexed citations
18.
Doerr, Benjamin & Sebastian Mayer. (2019). The recovery of ridge functions on the hypercube suffers from the curse\n of dimensionality. arXiv (Cornell University). 2 indexed citations
19.
Doerr, Benjamin & Marvin Künnemann. (2016). Improved Protocols and Hardness Results for the Two-Player\n Cryptogenography Problem. arXiv (Cornell University). 1 indexed citations
20.
Auger, Anne & Benjamin Doerr. (2011). Theory of Randomized Search Heuristics. 193 indexed citations

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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