Memetic Computing

381 papers and 6.5k indexed citations i.

About

The 381 papers published in Memetic Computing in the last decades have received a total of 6.5k indexed citations. Papers published in Memetic Computing usually cover Artificial Intelligence (252 papers), Computational Theory and Mathematics (140 papers) and Industrial and Manufacturing Engineering (65 papers) specifically the topics of Metaheuristic Optimization Algorithms Research (191 papers), Advanced Multi-Objective Optimization Algorithms (124 papers) and Evolutionary Algorithms and Applications (112 papers). The most active scholars publishing in Memetic Computing are Gai‐Ge Wang, Jagdish Chand Bansal, Harish Sharma, Shimpi Singh Jadon, Maurice Clerc, Ferrante Neri, Albert Y. S. Lam, Victor O. K. Li, Yew-Soon Ong and Ville Tirronen.

In The Last Decade

Fields of papers published in Memetic Computing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Memetic Computing. 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 Memetic Computing.

Countries where authors publish in Memetic Computing

Since Specialization
Citations

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