Frank Neumann

9.2k citations
272 papers · 4.5k indexed · h-index 36

Impact in

Papers in

Frank Neumann

255 papers receiving 4.4k citations

Peers

Frank Neumann
Comparison fields: 5 of 161
  • Computational Theory and Mathematics 1.9k
  • Artificial Intelligence 2.6k
  • Industrial and Manufacturing Engineering 746
  • Computer Networks and Communications 531
  • Management Science and Operations Research 285
Replace Zhang Yon with:
Zhang Yon China
Mingjing Wang China
Günter Rudolph Germany
Kevin Swersky United States
Yi Mei New Zealand
Zhenyu Yang Denmark
Jouni Lampinen Finland
Nikolaos V. Sahinidis United States
Millie Pant India
Wolf Fïchtner Germany
Frank Neumann relative to Zhang Yon China Zhang Yon's profile →
Citations per field
00.5×1.7×
Zhang Yon · 1×
Citations per year

Countries citing papers authored by Frank Neumann

Since Specialization
Citations

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

Fields of papers citing papers by Frank Neumann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Frank Neumann, 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 Frank Neumann Line = papers co-authored together Frank Neumann links everyone, so they are left out of the graph.

All Works

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Speeding up Evolutionary Algorithms by Restricted Mutation Operators.
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About Frank Neumann

Frank Neumann is a scholar working on Industrial and Manufacturing Engineering, Computational Theory and Mathematics, Artificial Intelligence, Computer Networks and Communications and Computer Graphics and Computer-Aided Design, having authored 272 papers that have together received 4.5k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (120 papers), Advanced Multi-Objective Optimization Algorithms (90 papers), Evolutionary Algorithms and Applications (65 papers), Vehicle Routing Optimization Methods (51 papers), Optimization and Packing Problems (26 papers), Optimization and Search Problems (19 papers), Constraint Satisfaction and Optimization (18 papers) and Complexity and Algorithms in Graphs (16 papers). The work is most often cited by research in Computational Theory and Mathematics (1.9k citations), Artificial Intelligence (2.6k citations), Industrial and Manufacturing Engineering (746 citations), Computer Networks and Communications (531 citations) and Management Science and Operations Research (285 citations). Frank Neumann has collaborated with scholars based in Australia, Germany and United Kingdom. Frequent co-authors include Carsten Witt, Tobias Friedrich, Markus Wagner, Ingo Wegener, Benjamin Doerr, Dirk Sudholt, Aneta Neumann, Heike Trautmann, Nils Hebbinghaus and Benjamin Doerr. Their work appears in journals such as Evolutionary Computation, Theoretical Computer Science, Algorithmica, Inorganic Chemistry and Journal of Organometallic Chemistry.

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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