Finite-Dimensional Variational Inequalities and Complementarity Problems
Impact in
Classified as
- Authors
- Francisco FacchineiJong‐Shi Pang
- Journal
- CERN Document Server (European Organization for Nuclear Research)
In The Last Decade
doi.org/10.1007/b97543 →Countries where authors are citing Finite-Dimensional Variational Inequalities and Complementarity Problems
This map shows the geographic impact of Finite-Dimensional Variational Inequalities and Complementarity Problems. 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 Finite-Dimensional Variational Inequalities and Complementarity Problems with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Finite-Dimensional Variational Inequalities and Complementarity Problems more than expected).
Fields of papers citing Finite-Dimensional Variational Inequalities and Complementarity Problems
This network shows the impact of Finite-Dimensional Variational Inequalities and Complementarity Problems. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Finite-Dimensional Variational Inequalities and Complementarity Problems.
About Finite-Dimensional Variational Inequalities and Complementarity Problems
This paper, published in 2004, received 1.8k indexed citations . Written by Francisco Facchinei and Jong‐Shi Pang covering the research area of Numerical Analysis, Applied Mathematics and Computational Theory and Mathematics. It is primarily cited by scholars working on Computational Theory and Mathematics (1.0k citations), Numerical Analysis (723 citations), Control and Systems Engineering (284 citations), Computational Mechanics (264 citations) and Computer Networks and Communications (238 citations). Published in CERN Document Server (European Organization for Nuclear Research).
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/b97543.