Wayne Pullan

955 citations
30 papers · 623 · h-index 14

Impact in

Papers in

Wayne Pullan

30 papers receiving 599 citations

Peers

Wayne Pullan
Comparison fields: 5 of 86
  • Computational Theory and Mathematics 280
  • Industrial and Manufacturing Engineering 111
  • Computer Networks and Communications 225
  • Artificial Intelligence 181
  • Statistical and Nonlinear Physics 66
Replace Johannes J. Schneider with:
Johannes J. Schneider Germany
Thore Husfeldt Denmark
Samuel Fiorini Belgium
Piotr Sankowski Poland
Janez Žerovnik Slovenia
Victor Chepoi France
Marcin Pilipczuk Poland
Andreas Björklund Sweden
Douglas R. Woodall United Kingdom
Vladimir Ejov Australia
Wayne Pullan relative to Johannes J. Schneider Germany Johannes J. Schneider's profile →
Citations per field
00.5×3.3×
Johannes J. Schneider · 1×
Citations per year

Countries citing papers authored by Wayne Pullan

Since Specialization
Citations

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

Fields of papers citing papers by Wayne Pullan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 17 scholars most cited alongside Wayne Pullan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Wayne Pullan Line = papers co-authored together Wayne Pullan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006104
2 200763
3 200752
4 200644
5 199741
6 201037
7 201537
8 199736
9 200934
10 200531
11 199725
12 200423
13 200821
14 201519
15 20138
16 20088
17 20217
18 20056
19 20024
20 20204

About Wayne Pullan

Wayne Pullan is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Computer Networks and Communications, Materials Chemistry and Molecular Biology, having authored 30 papers that have together received 623 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (8 papers), Optimization and Search Problems (7 papers), Metaheuristic Optimization Algorithms Research (6 papers), Machine Learning and Algorithms (5 papers), Computational Drug Discovery Methods (4 papers), Vehicle Routing Optimization Methods (4 papers), Machine Learning in Materials Science (4 papers) and Facility Location and Emergency Management (3 papers). The work is most often cited by research in Computational Theory and Mathematics (280 citations), Industrial and Manufacturing Engineering (111 citations), Computer Networks and Communications (225 citations), Artificial Intelligence (181 citations) and Statistical and Nonlinear Physics (66 citations). Wayne Pullan has collaborated with scholars based in Australia, Italy and United States. Frequent co-authors include Holger H. Hoos, Andrea Grosso, Marco Locatelli, Mauro Brunato, Franco Mascia, Yaoqi Zhou, Yuedong Yang, Peter Brown, Alan Wee‐Chung Liew and Steve Drew. Their work appears in journals such as Journal of Heuristics, Journal of Combinatorial Optimization, Journal of Computational Chemistry, Journal of Global Optimization and Bioinformatics.

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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