Marco Tomassini

2.5k citations
52 papers · 1.0k · h-index 16

Impact in

Papers in

    • Evolutionary Algorithms and Applications 35
    • Metaheuristic Optimization Algorithms Research 17
    • Neural Networks and Applications 5
    • Reinforcement Learning in Robotics 4
    • Cellular Automata and Applications 8
    • Advanced Multi-Objective Optimization Algorithms 4

Marco Tomassini

49 papers receiving 944 citations

Peers

Marco Tomassini
Comparison fields: 5 of 88
  • Artificial Intelligence 742
  • Computational Theory and Mathematics 301
  • Management Science and Operations Research 58
  • Industrial and Manufacturing Engineering 45
  • Genetics 91
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Citations per field
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Citations per year

Countries citing papers authored by Marco Tomassini

Since Specialization
Citations

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

Fields of papers citing papers by Marco Tomassini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997127
2 200193
3
Spatially Structured Evolutionary Algorithms: Artificial Evolution in Space and Time (Natural Computing Series)
200589
4 200384
5 200579
6 200572
7 201053
8 199749
9 199645
10 201836
11 199628
12 200427
13 200424
14 200620
15 200718
16 200716
17
Fitness Distance Correlation And Problem Difficulty For Genetic Programming
200215
18 202014
19 200313
20
A study of diversity in multipopulation genetic programming
200412

About Marco Tomassini

Marco Tomassini is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology, Genetics and Mechanical Engineering, having authored 52 papers that have together received 1.0k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (35 papers), Metaheuristic Optimization Algorithms Research (17 papers), Cellular Automata and Applications (8 papers), Gene Regulatory Network Analysis (6 papers), Neural Networks and Applications (5 papers), Evolution and Genetic Dynamics (4 papers), Reinforcement Learning in Robotics (4 papers) and Advanced Multi-Objective Optimization Algorithms (4 papers). The work is most often cited by research in Artificial Intelligence (742 citations), Computational Theory and Mathematics (301 citations), Management Science and Operations Research (58 citations), Industrial and Manufacturing Engineering (45 citations) and Genetics (91 citations). Marco Tomassini has collaborated with scholars based in Switzerland, Spain and France. Frequent co-authors include Leonardo Vanneschi, Andrea G. B. Tettamanzi, F.V. Fernández, Moshe Sipper, Eduardo García Sánchez, Philippe Collard, Manuel Clergue, Sebástien Vérel, Andrés Pérez-Uribe and Daniel Mange. Their work appears in journals such as Genetic Programming and Evolvable Machines, Theoretical Computer Science, IEEE Transactions on Evolutionary Computation, Parallel Computing and Artificial Life.

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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