Tapabrata Ray

9.1k citations
237 papers · 6.4k indexed · 1 hit paper · h-index 40
Topics
Advanced Multi-Objective Optimization Algorithms (126 papers)Metaheuristic Optimization Algorithms Research (82 papers)Evolutionary Algorithms and Applications (43 papers)

In The Last Decade

Tapabrata Ray

227 papers receiving 6.2k citations

Hit Papers

A Decomposition-Based Evolutionary Algorithm for Many Obj...2014202620182022201450100150200250

Peers

Tapabrata Ray
Comparison fields: 5 of 149
  • Computational Theory and Mathematics 3.3k
  • Artificial Intelligence 3.3k
  • Management Science and Operations Research 905
  • Control and Systems Engineering 803
  • Electrical and Electronic Engineering 672
Replace Bernhard Sendhoff with:
Bernhard Sendhoff Germany
Carlos M. Fonseca Portugal
Aimin Zhou China
Gary B. Lamont United States
Himanshu Jain India
David A. Van Veldhuizen United States
Shahrzad Saremi Australia
Kaisa Miettinen Finland
Ye Tian China
Tapabrata Ray relative to Bernhard Sendhoff Germany Bernhard Sendhoff's profile →
Citations per field
00.5×1.5×
Bernhard Sendhoff · 1×
Citations per year

Countries citing papers authored by Tapabrata Ray

Since Specialization
Citations

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

Fields of papers citing papers by Tapabrata Ray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tapabrata Ray. 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 Tapabrata Ray. The network helps show where Tapabrata Ray may publish in the future.

Co-authorship network of co-authors of Tapabrata Ray

This figure shows the co-authorship network connecting the top 25 collaborators of Tapabrata Ray. A scholar is included among the top collaborators of Tapabrata Ray 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 Tapabrata Ray. Tapabrata Ray is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 1
4 0
5 7
6 1
7 9
8 10
9 6
10 7
11 33
12 6
13 19
14 21
15 113
16 22
17 59
18 91
19 46
20 3

About Tapabrata Ray

Tapabrata Ray is a scholar working on Computational Theory and Mathematics, Statistics, Probability and Uncertainty and Management Science and Operations Research, having authored 237 papers that have together received 6.4k indexed citations. Recurring topics across this work include Advanced Multi-Objective Optimization Algorithms (126 papers), Metaheuristic Optimization Algorithms Research (82 papers) and Evolutionary Algorithms and Applications (43 papers). The work is most often cited by research in Computational Theory and Mathematics (3.3k citations), Artificial Intelligence (3.3k citations) and Management Science and Operations Research (905 citations). Tapabrata Ray has collaborated with scholars based in Australia, Singapore and United Kingdom. Frequent co-authors include Ruhul Sarker, Hemant Kumar Singh, K.M. Liew, Md Asafuddoula, Saber Elsayed, Kang Tai, Pankaj Saini, Warren Smith, Amitay Isaacs and Sreenatha G. Anavatti. Their work appears in journals such as PLoS ONE, Journal of Cleaner Production and Scientific Reports.

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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