Dirk Büche

852 total citations
9 papers, 545 citations indexed

About

Dirk Büche is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Dirk Büche has authored 9 papers receiving a total of 545 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computational Theory and Mathematics, 3 papers in Artificial Intelligence and 2 papers in Aerospace Engineering. Recurrent topics in Dirk Büche's work include Advanced Multi-Objective Optimization Algorithms (5 papers), Metaheuristic Optimization Algorithms Research (3 papers) and Evolutionary Algorithms and Applications (3 papers). Dirk Büche is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (5 papers), Metaheuristic Optimization Algorithms Research (3 papers) and Evolutionary Algorithms and Applications (3 papers). Dirk Büche collaborates with scholars based in Switzerland. Dirk Büche's co-authors include Petros Koumoutsakos, Nicol N. Schraudolph, Stefan Kern, Nikolaus Hansen, Rolf Dornberger, Sibylle D. Müller, Jiří Očenášek and Peter Stoll and has published in prestigious journals such as Natural Computing, IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) and Repository for Publications and Research Data (ETH Zurich).

In The Last Decade

Dirk Büche

9 papers receiving 513 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dirk Büche Switzerland 6 342 309 64 59 43 9 545
Bas van Stein Netherlands 14 217 0.6× 161 0.5× 38 0.6× 53 0.9× 53 1.2× 57 491
Muhammad Asif Jan Pakistan 14 332 1.0× 309 1.0× 147 2.3× 59 1.0× 129 3.0× 35 687
Wei Zeng China 11 247 0.7× 264 0.9× 93 1.5× 20 0.3× 41 1.0× 41 609
Giampaolo Liuzzi Italy 17 219 0.6× 452 1.5× 58 0.9× 60 1.0× 118 2.7× 58 836
Marat S. Mukhametzhanov Italy 13 185 0.5× 305 1.0× 24 0.4× 23 0.4× 62 1.4× 27 586
Genetha A. Gray United States 8 135 0.4× 187 0.6× 20 0.3× 51 0.9× 14 0.3× 24 405
G. Lallement United States 14 232 0.7× 676 2.2× 57 0.9× 129 2.2× 15 0.3× 63 992
D. Finkel United States 7 117 0.3× 155 0.5× 29 0.5× 38 0.6× 24 0.6× 8 403
Raymond Ros France 10 671 2.0× 481 1.6× 18 0.3× 45 0.8× 34 0.8× 21 795
Shan Ba United States 9 108 0.3× 261 0.8× 55 0.9× 200 3.4× 23 0.5× 15 524

Countries citing papers authored by Dirk Büche

Since Specialization
Citations

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

Fields of papers citing papers by Dirk Büche

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dirk Büche

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

All Works

9 of 9 papers shown
2.
Büche, Dirk, Nicol N. Schraudolph, & Petros Koumoutsakos. (2005). Accelerating Evolutionary Algorithms With Gaussian Process Fitness Function Models. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews). 35(2). 183–194. 249 indexed citations
3.
Kern, Stefan, Sibylle D. Müller, Nikolaus Hansen, et al.. (2004). Learning probability distributions in continuous evolutionary algorithms – a comparative review. Natural Computing. 3(1). 77–112. 164 indexed citations
4.
Kern, Stefan, Sibylle D. Müller, Nikolaus Hansen, et al.. (2004). Learning Probability Distributions in Continuous Evolutionary Algorithms - a Comparative Review. Natural Computing. 3(3). 355–356. 13 indexed citations
5.
Büche, Dirk. (2003). Multi-objective evolutionary optimization of gas turbine components. Repository for Publications and Research Data (ETH Zurich). 8 indexed citations
6.
Büche, Dirk, Peter Stoll, Rolf Dornberger, & Petros Koumoutsakos. (2002). Multiobjective evolutionary algorithm for the optimization of noisy combustion processes. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews). 32(4). 460–473. 91 indexed citations
7.
Dornberger, Rolf & Dirk Büche. (2001). New Evolutionary Algorithm for Multi-objective Optimization and the Application to Engineering Design Problems.. 3 indexed citations
8.
Dornberger, Rolf, Dirk Büche, & Peter Stoll. (2000). MULTIDISCIPLINARY OPTIMIZATION IN TURBOMACHINERY DESIGN. 15 indexed citations
9.
Dornberger, Rolf & Dirk Büche. (1999). Multidisciplinary and Multiobjective Optimization Applied to Turbine Design. Technical Report, ABB ALSTOM POWER AAT-1999-5, T2-99-22, Baden. 1 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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