Shuffled complex evolution approach for effective and efficient global minimization
In The Last Decade
doi.org/10.1007/bf00939380 →Countries where authors are citing Shuffled complex evolution approach for effective and efficient global minimization
This map shows the geographic impact of Shuffled complex evolution approach for effective and efficient global minimization. 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 Shuffled complex evolution approach for effective and efficient global minimization with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuffled complex evolution approach for effective and efficient global minimization more than expected).
Fields of papers citing Shuffled complex evolution approach for effective and efficient global minimization
This network shows the impact of Shuffled complex evolution approach for effective and efficient global minimization. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Shuffled complex evolution approach for effective and efficient global minimization.
About Shuffled complex evolution approach for effective and efficient global minimization
This paper, published in 1993, received 1.3k indexed citations . Written by Qingyun Duan, Vijai Kumar Gupta and Soroosh Sorooshian covering the research area of Computational Theory and Mathematics, Ocean Engineering and Artificial Intelligence. It is primarily cited by scholars working on Water Science and Technology (703 citations), Global and Planetary Change (601 citations) and Environmental Engineering (416 citations). Published in Journal of Optimization Theory and Applications.
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/10.1007/bf00939380.