Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
In The Last Decade
doi.org/w68008043 →Countries where authors are citing Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
This map shows the geographic impact of Multiobjective evolutionary algorithms: classifications, analyses, and new innovations. 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 Multiobjective evolutionary algorithms: classifications, analyses, and new innovations with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Multiobjective evolutionary algorithms: classifications, analyses, and new innovations more than expected).
Fields of papers citing Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
This network shows the impact of Multiobjective evolutionary algorithms: classifications, analyses, and new innovations. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Multiobjective evolutionary algorithms: classifications, analyses, and new innovations.
About Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
This paper, published in 1999, received 908 indexed citations . Written by Gary B. Lamont and David A. Van Veldhuizen covering the research area of Computational Theory and Mathematics and Artificial Intelligence. It is primarily cited by scholars working on Computational Theory and Mathematics (644 citations), Artificial Intelligence (541 citations) and Industrial and Manufacturing Engineering (121 citations).
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.
This paper is also available at doi.org/w68008043.