A new polynomial-time algorithm for linear programming

2.9k indexed citations

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This paper, published in 1984, received 2.9k indexed citations. Written by Narendra Karmarkar covering the research area of Computer Graphics and Computer-Aided Design and Computational Theory and Mathematics. It is primarily cited by scholars working on Computational Theory and Mathematics (1.5k citations), Numerical Analysis (1.2k citations) and Computer Networks and Communications (474 citations). Published in COMBINATORICA.

Countries where authors are citing A new polynomial-time algorithm for linear programming

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This map shows the geographic impact of A new polynomial-time algorithm for linear programming. 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 A new polynomial-time algorithm for linear programming with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A new polynomial-time algorithm for linear programming more than expected).

Fields of papers citing A new polynomial-time algorithm for linear programming

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of A new polynomial-time algorithm for linear programming. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the A new polynomial-time algorithm for linear programming.

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/bf02579150.

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