Pranab Biswas

24 total papers · 1.4k total citations
18 papers, 894 citations indexed

About

Pranab Biswas is a scholar working on Management Science and Operations Research, Control and Systems Engineering and Statistics and Probability. According to data from OpenAlex, Pranab Biswas has authored 18 papers receiving a total of 894 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Management Science and Operations Research, 13 papers in Control and Systems Engineering and 7 papers in Statistics and Probability. Recurrent topics in Pranab Biswas's work include Multi-Criteria Decision Making (17 papers), Optimization and Mathematical Programming (13 papers) and Fuzzy Systems and Optimization (7 papers). Pranab Biswas is often cited by papers focused on Multi-Criteria Decision Making (17 papers), Optimization and Mathematical Programming (13 papers) and Fuzzy Systems and Optimization (7 papers). Pranab Biswas collaborates with scholars based in India. Pranab Biswas's co-authors include Bibhas C. Giri, Surapati Pramanik, David M. Halliday, B. Conway, Simon F. Farmer and Rosenberg and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Neural Computing and Applications.

In The Last Decade

Pranab Biswas

18 papers receiving 787 citations

Hit Papers

TOPSIS method for multi-a... 2015 2026 2018 2022 2015 2022 50 100 150 200 250

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Pranab Biswas 715 416 172 151 117 18 894
Pu Ji 628 0.9× 323 0.8× 137 0.8× 232 1.5× 81 0.7× 26 927
J. Siskos 645 0.9× 200 0.5× 121 0.7× 204 1.4× 150 1.3× 17 960
Adjei Peter Darko 603 0.8× 284 0.7× 180 1.0× 118 0.8× 167 1.4× 37 932
Xin Zhang 549 0.8× 281 0.7× 168 1.0× 115 0.8× 176 1.5× 51 988
Pushpinder Singh 729 1.0× 430 1.0× 374 2.2× 180 1.2× 152 1.3× 41 907
Xiaohan Yu 581 0.8× 289 0.7× 161 0.9× 202 1.3× 130 1.1× 36 766
Cengiz Kahraman 561 0.8× 215 0.5× 107 0.6× 104 0.7× 104 0.9× 14 817
Vahid Mohagheghi 711 1.0× 271 0.7× 118 0.7× 82 0.5× 66 0.6× 45 902
Jing–Rong Chang 630 0.9× 215 0.5× 180 1.0× 237 1.6× 98 0.8× 32 960
Fang Jin 715 1.0× 329 0.8× 241 1.4× 138 0.9× 158 1.4× 14 852

Countries citing papers authored by Pranab Biswas

Since Specialization
Citations

This map shows the geographic impact of Pranab Biswas's research. 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 Pranab Biswas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pranab Biswas more than expected).

Fields of papers citing papers by Pranab Biswas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pranab Biswas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Pranab Biswas. The network helps show where Pranab Biswas may publish in the future.

Co-authorship network of co-authors of Pranab Biswas

This figure shows the co-authorship network connecting the top 25 collaborators of Pranab Biswas. A scholar is included among the top collaborators of Pranab Biswas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Pranab Biswas. Pranab Biswas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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