Leila Kallel

663 citations
16 papers · 535 · h-index 10

Impact in

Papers in

Leila Kallel

16 papers receiving 499 citations

Peers

Leila Kallel
Comparison fields: 5 of 66
  • Computational Theory and Mathematics 234
  • Artificial Intelligence 401
  • Industrial and Manufacturing Engineering 34
  • Genetics 67
  • Computer Networks and Communications 56
Replace Jayshree Sarma with:
Jayshree Sarma United States
N. Franken South Africa
Piet Spiessens Belgium
Martin S. Krejca Germany
Scott Davies United States
Christian W. G. Lasarczyk Germany
Benjamin Doerr France
Gideon Ehrlich Israel
Luís M. S.​Russo Portugal
Felix Streichert Germany
Leila Kallel relative to Jayshree Sarma United States Jayshree Sarma's profile →
Citations per field
00.5×2×3×4×4.7×
Jayshree Sarma · 1×
Citations per year

Countries citing papers authored by Leila Kallel

Since Specialization
Citations

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

Fields of papers citing papers by Leila Kallel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 9 scholars most cited alongside Leila Kallel, 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 Leila Kallel Line = papers co-authored together Leila Kallel links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 1999130
2 2000126
3 200187
4 200140
5
Alternative Random Initialization in Genetic Algorithms.
199730
6 199624
7 200124
8 200021
9 200113
10 199710
11 19987
12 20037
13
Candidate Longpaths for the Simple Genetic Algorithm.
19986
14 20064
15
Convergence des algorithmes genetiques : aspects spatiaux et temporels
19993
16 19983

About Leila Kallel

Leila Kallel is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Signal Processing, Civil and Structural Engineering and Bioengineering, having authored 16 papers that have together received 535 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (11 papers), Evolutionary Algorithms and Applications (9 papers), Advanced Multi-Objective Optimization Algorithms (3 papers), Fuzzy Logic and Control Systems (2 papers), Data Management and Algorithms (2 papers), Structural Health Monitoring Techniques (2 papers), Approximation Theory and Sequence Spaces (1 paper) and Diffusion and Search Dynamics (1 paper). The work is most often cited by research in Computational Theory and Mathematics (234 citations), Artificial Intelligence (401 citations), Industrial and Manufacturing Engineering (34 citations), Genetics (67 citations) and Computer Networks and Communications (56 citations). Leila Kallel has collaborated with scholars based in France, Belgium and United Kingdom. Frequent co-authors include Bart Naudts, Josselin C. Garnier, Marc Schoenauer, Colin R. Reeves, François Jouve, Jonathan E. Rowe, Pierre Del Moral, Patricia Aïssa and H. Trabelsi. Their work appears in journals such as IEEE Transactions on Evolutionary Computation, Journal of Separation Science, SIAM Journal on Discrete Mathematics, Evolutionary Computation and Natural computing series.

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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