Evolutionary Computation

681 papers and 47.8k indexed citations i.

About

The 681 papers published in Evolutionary Computation in the last decades have received a total of 47.8k indexed citations. Papers published in Evolutionary Computation usually cover Artificial Intelligence (539 papers), Computational Theory and Mathematics (298 papers) and Molecular Biology (64 papers) specifically the topics of Metaheuristic Optimization Algorithms Research (437 papers), Evolutionary Algorithms and Applications (393 papers) and Advanced Multi-Objective Optimization Algorithms (265 papers). The most active scholars publishing in Evolutionary Computation are Kalyanmoy Deb, N. Srinivas, Eckart Zitzler, Nikolaus Hansen, Lothar Thiele, Andreas Ostermeier, Kenneth O. Stanley, Zbigniew Michalewicz, Risto Miikkulainen and Heinz Mühlenbein.

In The Last Decade

Fields of papers published in Evolutionary Computation

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Evolutionary Computation. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Evolutionary Computation.

Countries where authors publish in Evolutionary Computation

Since Specialization
Citations

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

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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2025