Ami Arbel

1.7k citations
55 papers · 1.3k · h-index 17

Impact in

Papers in

Ami Arbel

51 papers receiving 1.2k citations

Peers

Ami Arbel
Comparison fields: 5 of 98
  • Management Science and Operations Research 572
  • Control and Systems Engineering 554
  • Numerical Analysis 108
  • Statistics and Probability 138
  • Computational Theory and Mathematics 244
Replace M.G. Singh with:
M.G. Singh United Kingdom
Po-Lung Yu United States
Cerry M. Klein United States
G. Bojadziev Canada
Waldemar W. Koczkodaj Canada
Thomas Feuring Germany
Gerd Bohlender Germany
Eduardo Conde Spain
Behnam Malakooti United States
Ami Arbel relative to M.G. Singh United Kingdom M.G. Singh's profile →
Citations per field
00.5×2×3.2×
M.G. Singh · 1×
Citations per year

Countries citing papers authored by Ami Arbel

Since Specialization
Citations

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

Fields of papers citing papers by Ami Arbel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Ami Arbel, 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 Ami Arbel Line = papers co-authored together Ami Arbel links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1977230
2 1989211
3 1993127
4 198495
5 198193
6 199076
7 198162
8 198230
9 199227
10 198423
11 198221
12 198320
13 198418
14 198417
15 199416
16 199316
17 197916
18 199315
19 198614
20 198614

About Ami Arbel

Ami Arbel is a scholar working on Control and Systems Engineering, Computational Theory and Mathematics, Numerical Analysis, Management Science and Operations Research and Industrial and Manufacturing Engineering, having authored 55 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Optimization Algorithms Research (14 papers), Advanced Control Systems Optimization (11 papers), Optimization and Mathematical Programming (10 papers), Advanced Multi-Objective Optimization Algorithms (10 papers), Multi-Criteria Decision Making (8 papers), Scheduling and Optimization Algorithms (5 papers), Control Systems and Identification (4 papers) and Dynamics and Control of Mechanical Systems (4 papers). The work is most often cited by research in Management Science and Operations Research (572 citations), Control and Systems Engineering (554 citations), Numerical Analysis (108 citations), Statistics and Probability (138 citations) and Computational Theory and Mathematics (244 citations). Ami Arbel has collaborated with scholars based in Israel and United States. Frequent co-authors include David G. Luenberger, Abraham Seidmann, Luís G. Vargas, Yair E. Orgler, N.K. Gupta, Shmuel S. Oren, Edison Tse, Richard M. Tong, Pekka Korhonen and Yoram Shapira. Their work appears in journals such as Journal of the Operational Research Society, European Journal of Operational Research, International Journal of Control, IEEE Transactions on Automatic Control and Computers & Operations Research.

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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