Martin Zaefferer

832 citations
24 papers · 258 indexed · h-index 7
Topics
Advanced Multi-Objective Optimization Algorithms (16 papers)Metaheuristic Optimization Algorithms Research (9 papers)Evolutionary Algorithms and Applications (5 papers)
Partner nations
GermanyUnited Kingdom

In The Last Decade

Martin Zaefferer

23 papers receiving 246 citations

Peers

Martin Zaefferer
Comparison fields: 5 of 74
  • Artificial Intelligence 129
  • Computational Theory and Mathematics 116
  • Management Science and Operations Research 47
  • Industrial and Manufacturing Engineering 32
  • Mechanical Engineering 24
Replace Yoel Tenne with:
Yoel Tenne Israel
Yeboon Yun Japan
Jörg Stork Germany
Daniel Jaeggi United Kingdom
Ting‐Yu Chen Taiwan
Jinglu Li China
Y. Yang China
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David Parker United Kingdom
Philipp Limbourg Germany
Martin Zaefferer relative to Yoel Tenne Israel Yoel Tenne's profile →
Citations per field
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Countries citing papers authored by Martin Zaefferer

Since Specialization
Citations

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

Fields of papers citing papers by Martin Zaefferer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Zaefferer

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Zaefferer. A scholar is included among the top collaborators of Martin Zaefferer 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 Martin Zaefferer. Martin Zaefferer 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
#WorkIndexed citations
1 3
2 22
3 2
4 6
5 18
6 5
7
In a Nutshell: Sequential Parameter Optimization
3
8 2
9 111
10 15
11 33
12 4
13
Simulation and Optimization of Cyclone Dust Separators
1
14 1
15 1
16 2
17 0
18 3
19
Ensemble Based Optimization and Tuning Algorithms
2
20 5

About Martin Zaefferer

Martin Zaefferer is a scholar working on Computational Theory and Mathematics, Management Science and Operations Research and Artificial Intelligence, having authored 24 papers that have together received 258 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (16 papers), Metaheuristic Optimization Algorithms Research (9 papers) and Evolutionary Algorithms and Applications (5 papers). The work is most often cited by research in Computational Theory and Mathematics (116 citations), Artificial Intelligence (129 citations) and Management Science and Operations Research (47 citations). Martin Zaefferer has collaborated with scholars based in Germany and United Kingdom. Frequent co-authors include Thomas Bartz–Beielstein, Jörg Stork, Boris Naujoks, Andreas Fischbach, Olaf Mersmann, Daniel Gaida, Günter Rudolph, Wolfgang Konen, Quoc Cuong Pham and Patrick Koch. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Evolutionary Computation and Applied Soft Computing.

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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