Frédéric Lardeux

658 citations
41 papers · 448 · h-index 10

Impact in

Papers in

Frédéric Lardeux

38 papers receiving 436 citations

Peers

Frédéric Lardeux
Comparison fields: 5 of 63
  • Computational Theory and Mathematics 150
  • Artificial Intelligence 213
  • Industrial and Manufacturing Engineering 62
  • Computer Networks and Communications 103
  • Plant Science 130
Replace Petr Kolman with:
Petr Kolman Czechia
Michael Zapf Germany
Jessica Andrea Carballido Argentina
Camilo Rocha Colombia
Álvaro Rubio‐Largo Spain
Vivek Kumar Sharma India
Ranjan Sinha Australia
Liliana Ironi Italy
Frédéric Lardeux relative to Petr Kolman Czechia Petr Kolman's profile →
Citations per field
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Citations per year

Countries citing papers authored by Frédéric Lardeux

Since Specialization
Citations

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

Fields of papers citing papers by Frédéric Lardeux

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009107
2 201067
3 200662
4 201031
5 201224
6 200318
7 201514
8 201113
9
A Hybrid Genetic Algorithm for the Satisfiability Problem
200211
10 200910
11 20158
12 20188
13 20248
14 20197
15 20176
16 20176
17 20095
18 20154
19 20214
20 20223

About Frédéric Lardeux

Frédéric Lardeux is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Management Science and Operations Research and Industrial and Manufacturing Engineering, having authored 41 papers that have together received 448 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (15 papers), Constraint Satisfaction and Optimization (12 papers), Machine Learning and Algorithms (7 papers), Evolutionary Algorithms and Applications (7 papers), semigroups and automata theory (7 papers), Formal Methods in Verification (6 papers), Model-Driven Software Engineering Techniques (4 papers) and Algorithms and Data Compression (4 papers). The work is most often cited by research in Computational Theory and Mathematics (150 citations), Artificial Intelligence (213 citations), Industrial and Manufacturing Engineering (62 citations), Computer Networks and Communications (103 citations) and Plant Science (130 citations). Frédéric Lardeux has collaborated with scholars based in France, Chile and Poland. Frequent co-authors include Frédéric Saubion, Jin‐Kao Hao, Adrien Goëffon, Tristan Boureau, Stéphane Poussier, Ahmed Hajri, Chrystelle Brin, Charles Manceau, Gilles Hunault and Christophe Lemaire. Their work appears in journals such as PLoS ONE, IEEE Access, Applied Soft Computing, Lecture notes in computer science and Journal of Heuristics.

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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