Mardé Helbig

656 citations
29 papers · 379 · h-index 10

Impact in

Papers in

Mardé Helbig

27 papers receiving 376 citations

Peers

Mardé Helbig
Comparison fields: 5 of 37
  • Computational Theory and Mathematics 317
  • Artificial Intelligence 321
  • Management Science and Operations Research 61
  • Industrial and Manufacturing Engineering 26
  • Control and Systems Engineering 54
Replace Kaname Narukawa with:
Kaname Narukawa Japan
Naoya Akedo Japan
Jiawei Yuan China
Heiner Zille Germany
Yuji Sakane Japan
Ma. Guadalupe Castillo Tapia Mexico
Jesús Guillermo Falcón-Cardona Mexico
Gan Ruan United Kingdom
Jiajie Mo China
Mardé Helbig relative to Kaname Narukawa Japan Kaname Narukawa's profile →
Citations per field
00.5×1.5×
Kaname Narukawa · 1×
Citations per year

Countries citing papers authored by Mardé Helbig

Since Specialization
Citations

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

Fields of papers citing papers by Mardé Helbig

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 6 scholars most cited alongside Mardé Helbig, 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 Mardé Helbig Line = papers co-authored together Mardé Helbig links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201378
2 201449
3 201338
4 201135
5 201332
6 201329
7 201225
8 201319
9 201614
10 201413
11 20179
12 20167
13 20185
14 20104
15 20173
16 20193
17 20232
18 20152
19 20182
20 20172

About Mardé Helbig

Mardé Helbig is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Management Science and Operations Research, Control and Systems Engineering and Statistics, Probability and Uncertainty, having authored 29 papers that have together received 379 indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (24 papers), Metaheuristic Optimization Algorithms Research (22 papers), Evolutionary Algorithms and Applications (11 papers), Optimal Experimental Design Methods (5 papers), Process Optimization and Integration (4 papers), Probabilistic and Robust Engineering Design (3 papers), Machine Learning and ELM (3 papers) and Stock Market Forecasting Methods (2 papers). The work is most often cited by research in Computational Theory and Mathematics (317 citations), Artificial Intelligence (321 citations), Management Science and Operations Research (61 citations), Industrial and Manufacturing Engineering (26 citations) and Control and Systems Engineering (54 citations). Mardé Helbig has collaborated with scholars based in South Africa, Australia and Germany. Frequent co-authors include Andries P. Engelbrecht, Kalyanmoy Deb, Dong‐Zhi Sun, Tanja Clees, Heiner Zille and Sanaz Mostaghim. Their work appears in journals such as ACM Computing Surveys, Neural Computing and Applications, International Journal of Material Forming, Swarm and Evolutionary Computation and Information Sciences.

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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