Ali Asghar Foroughi

636 total citations
26 papers, 529 citations indexed

About

Ali Asghar Foroughi is a scholar working on Management Science and Operations Research, Control and Systems Engineering and Numerical Analysis. According to data from OpenAlex, Ali Asghar Foroughi has authored 26 papers receiving a total of 529 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Management Science and Operations Research, 12 papers in Control and Systems Engineering and 3 papers in Numerical Analysis. Recurrent topics in Ali Asghar Foroughi's work include Efficiency Analysis Using DEA (19 papers), Multi-Criteria Decision Making (15 papers) and Optimization and Mathematical Programming (12 papers). Ali Asghar Foroughi is often cited by papers focused on Efficiency Analysis Using DEA (19 papers), Multi-Criteria Decision Making (15 papers) and Optimization and Mathematical Programming (12 papers). Ali Asghar Foroughi collaborates with scholars based in Iran, Canada and United Kingdom. Ali Asghar Foroughi's co-authors include A. Hadi‐Vencheh, Mehrdad Tamiz, Joe Zhu, Majid Soleimani-damaneh, G.R. Jahanshahloo, Reza Kazemi Matin, Belaı̈d Aouni, Dylan Jones, Masoud Zarepisheh and Mohammad Tavassoli and has published in prestigious journals such as European Journal of Operational Research, Expert Systems with Applications and International Journal of Production Research.

In The Last Decade

Ali Asghar Foroughi

26 papers receiving 503 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ali Asghar Foroughi Iran 11 468 183 158 54 46 26 529
Yiannis Smirlis Greece 10 442 0.9× 139 0.8× 175 1.1× 53 1.0× 34 0.7× 19 571
Shabnam Razavyan Iran 11 382 0.8× 150 0.8× 166 1.1× 62 1.1× 38 0.8× 32 476
N. Shoja Iran 13 440 0.9× 160 0.9× 186 1.2× 72 1.3× 41 0.9× 29 512
Ruiyue Lin China 17 527 1.1× 304 1.7× 113 0.7× 70 1.3× 32 0.7× 31 595
Emran Mohammadi Iran 13 413 0.9× 199 1.1× 143 0.9× 49 0.9× 70 1.5× 61 667
Gholam Reza Jahanshahloo Iran 9 427 0.9× 127 0.7× 190 1.2× 66 1.2× 34 0.7× 23 468
Ghasem Tohidi Iran 14 468 1.0× 197 1.1× 171 1.1× 71 1.3× 48 1.0× 56 558
Mehdi Soltanifar Iran 14 415 0.9× 97 0.5× 204 1.3× 44 0.8× 65 1.4× 37 578
Nazila Aghayi Iran 8 297 0.6× 101 0.6× 125 0.8× 39 0.7× 26 0.6× 19 330

Countries citing papers authored by Ali Asghar Foroughi

Since Specialization
Citations

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

Fields of papers citing papers by Ali Asghar Foroughi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ali Asghar Foroughi. 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 Ali Asghar Foroughi. The network helps show where Ali Asghar Foroughi may publish in the future.

Co-authorship network of co-authors of Ali Asghar Foroughi

This figure shows the co-authorship network connecting the top 25 collaborators of Ali Asghar Foroughi. A scholar is included among the top collaborators of Ali Asghar Foroughi 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 Ali Asghar Foroughi. Ali Asghar Foroughi 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
1.
Foroughi, Ali Asghar, et al.. (2024). A compromise programming approach for cross efficiency measurement in basic two-stage network system. Expert Systems with Applications. 252. 124205–124205. 1 indexed citations
2.
Foroughi, Ali Asghar, et al.. (2022). Evaluating the Efficiency of Decision Making Units in Fuzzy two-stage DEA Models. Fuzzy Information and Engineering. 14(3). 291–313. 3 indexed citations
3.
Foroughi, Ali Asghar, et al.. (2019). Inverse optimization for multi-objective linear programming. Optimization Letters. 13(2). 281–294. 9 indexed citations
4.
Foroughi, Ali Asghar & Mohammad Tavassoli. (2018). Discriminating extreme efficient decision making units in DEA using random weight vectors. Computers & Industrial Engineering. 128. 305–312. 3 indexed citations
5.
Foroughi, Ali Asghar, et al.. (2017). Ranking efficient decision making units in data envelopment analysis based on reference frontier share. European Journal of Operational Research. 264(2). 665–674. 15 indexed citations
6.
Foroughi, Ali Asghar, et al.. (2016). Decomposition weights and overall efficiency in two-stage additive network DEA. European Journal of Operational Research. 257(3). 896–906. 116 indexed citations
7.
Foroughi, Ali Asghar. (2012). A revised and generalized model with improved discrimination for finding most efficient DMUs in DEA. Applied Mathematical Modelling. 37(6). 4067–4074. 8 indexed citations
8.
Foroughi, Ali Asghar. (2011). A modified common weight model for maximum discrimination in technology selection. International Journal of Production Research. 50(14). 3841–3846. 15 indexed citations
9.
Foroughi, Ali Asghar & Belaı̈d Aouni. (2011). New approaches for determining a common set of weights for a voting system. International Transactions in Operational Research. 19(4). 521–530. 15 indexed citations
10.
Foroughi, Ali Asghar & Belaı̈d Aouni. (2011). Ranking units in DEA based on efficiency intervals and decision‐maker's preferences. International Transactions in Operational Research. 19(4). 567–579. 7 indexed citations
11.
Foroughi, Ali Asghar. (2011). A note on “A new method for ranking discovered rules from data mining by DEA”, and a full ranking approach. Expert Systems with Applications. 38(10). 12913–12916. 5 indexed citations
12.
Foroughi, Ali Asghar. (2010). A new mixed integer linear model for selecting the best decision making units in data envelopment analysis. Computers & Industrial Engineering. 60(4). 550–554. 32 indexed citations
13.
Foroughi, Ali Asghar, et al.. (2008). A modified method for constructing efficient solutions structure of MOLP. Applied Mathematical Modelling. 33(5). 2403–2410. 8 indexed citations
14.
Tamiz, Mehrdad & Ali Asghar Foroughi. (2007). An enhanced approach to the ranked voting system. World Review of Entrepreneurship Management and Sustainable Development. 3(3/4). 365–365. 1 indexed citations
15.
Hadi‐Vencheh, A. & Ali Asghar Foroughi. (2006). A generalized DEA model for inputs/outputs estimation. Mathematical and Computer Modelling. 43(5-6). 447–457. 53 indexed citations
16.
Foroughi, Ali Asghar, Dylan Jones, & Mehrdad Tamiz. (2004). A selection method for a preferential election. Applied Mathematics and Computation. 163(1). 107–116. 25 indexed citations
17.
Soleimani-damaneh, Majid, G.R. Jahanshahloo, & Ali Asghar Foroughi. (2004). A comment on “Measuring super-efficiency in DEA in the presence of infeasibility”. European Journal of Operational Research. 170(1). 323–325. 6 indexed citations
18.
Foroughi, Ali Asghar & Mehrdad Tamiz. (2004). An effective total ranking model for a ranked voting system. Omega. 33(6). 491–496. 55 indexed citations
19.
Foroughi, Ali Asghar. (2004). A selection method for a preferential election. Applied Mathematics and Computation. 1 indexed citations
20.
Jahanshahloo, G.R., A. Hadi‐Vencheh, Ali Asghar Foroughi, & Reza Kazemi Matin. (2003). Inputs/outputs estimation in DEA when some factors are undesirable. Applied Mathematics and Computation. 156(1). 19–32. 43 indexed citations

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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