S. Vajda

70 papers receiving 5.2k citations

S. Vajda's Hit Papers

Mathematical Programming: Theory and Algorithms. 1987 · 439 citations
4390+22+45Years since publication250500750

Peers

S. Vajda
Comparison fields: 5 of 185
  • Numerical Analysis 890
  • Computational Theory and Mathematics 1.6k
  • Industrial and Manufacturing Engineering 928
  • Management Science and Operations Research 1.1k
  • General Decision Sciences 103
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Countries citing papers authored by S. Vajda

Since Specialization
Citations

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

Fields of papers citing papers by S. Vajda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside S. Vajda, 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 S. Vajda Line = papers co-authored together S. Vajda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Linear Programming and Extensions.
Hit paper breakdown →
1964806
2
Integer Programming and Network Flows.
Hit paper breakdown →
1970530
3
Graphs And Algorithms
1984497
4
Mathematical Programming: Theory and Algorithms.
Hit paper breakdown →
1987439
5 1960433
6
Games and Decisions: Introduction and Critical Survey.
Hit paper breakdown →
1958384
7 1995330
8 1964329
9 1964224
10
Fibonacci and Lucas Numbers, and the Golden Section: Theory and Applications
1989218
11 1995188
12 1973179
13 1951153
14 1959129
15 1970105
16 1972104
17 1958102
18 196995
19 197292
20 198372

About S. Vajda

S. Vajda is a scholar working on Management Science and Operations Research, Numerical Analysis, Artificial Intelligence, Computational Theory and Mathematics and Control and Systems Engineering, having authored 71 papers that have together received 5.9k indexed citations. Recurring topics across this work include Advanced Optimization Algorithms Research (9 papers), Game Theory and Applications (8 papers), Artificial Intelligence in Games (5 papers), Optimization and Mathematical Programming (3 papers), Logic, Reasoning, and Knowledge (3 papers), Advanced Mathematical Theories (2 papers), Data Management and Algorithms (2 papers) and Guidance and Control Systems (2 papers). The work is most often cited by research in Numerical Analysis (890 citations), Computational Theory and Mathematics (1.6k citations), Industrial and Manufacturing Engineering (928 citations), Management Science and Operations Research (1.1k citations) and General Decision Sciences (103 citations). S. Vajda has collaborated with scholars based in United Kingdom, United States and Malta. Frequent co-authors include George B. Dantzig, Michel Minoux, Brian Conolly, Samuel Karlin, Michel Gondran, David K. Smith, Howard Raiffa, R. Duncan Luce, Philip Wolfe and Harvey M. Wagner. Their work appears in journals such as Journal of the Operational Research Society, Journal of the American Statistical Association, Econometrica, Physics Today and Journal of the Royal Statistical Society Series C (Applied Statistics).

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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