F. Hooshmand

446 total citations
38 papers, 288 citations indexed

About

F. Hooshmand is a scholar working on Management Science and Operations Research, Automotive Engineering and Industrial and Manufacturing Engineering. According to data from OpenAlex, F. Hooshmand has authored 38 papers receiving a total of 288 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Management Science and Operations Research, 10 papers in Automotive Engineering and 10 papers in Industrial and Manufacturing Engineering. Recurrent topics in F. Hooshmand's work include Risk and Portfolio Optimization (10 papers), Vehicle Routing Optimization Methods (9 papers) and Transportation and Mobility Innovations (8 papers). F. Hooshmand is often cited by papers focused on Risk and Portfolio Optimization (10 papers), Vehicle Routing Optimization Methods (9 papers) and Transportation and Mobility Innovations (8 papers). F. Hooshmand collaborates with scholars based in Iran and Portugal. F. Hooshmand's co-authors include S.​A. MirHassani, Meysam Hosseini, Sirous Moradi, Susana Relvas, Maryam Bayat, M. Bayat and Zahra Zare and has published in prestigious journals such as Applied Energy, Expert Systems with Applications and Environmental Science and Pollution Research.

In The Last Decade

F. Hooshmand

34 papers receiving 283 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
F. Hooshmand Iran 11 95 89 81 49 45 38 288
Lihui Bai United States 10 88 0.9× 79 0.9× 70 0.9× 44 0.9× 23 0.5× 36 276
Alexander Vinel United States 11 62 0.7× 27 0.3× 76 0.9× 53 1.1× 50 1.1× 32 312
F. Javier Martín-Campo Spain 11 71 0.7× 83 0.9× 21 0.3× 63 1.3× 30 0.7× 19 424
Yusuf Kuvvetli Türkiye 10 44 0.5× 82 0.9× 40 0.5× 21 0.4× 44 1.0× 34 290
Ertan Yakıcı Türkiye 10 41 0.4× 149 1.7× 65 0.8× 52 1.1× 21 0.5× 24 338
Fábio Luiz Usberti Brazil 11 32 0.3× 123 1.4× 131 1.6× 60 1.2× 13 0.3× 36 336
Mir Ehsan Hesam Sadati Türkiye 10 159 1.7× 282 3.2× 65 0.8× 20 0.4× 23 0.5× 18 394
Safa Bhar Layeb Tunisia 8 84 0.9× 94 1.1× 101 1.2× 18 0.4× 49 1.1× 48 284
Ammar Al‐Bazi United Kingdom 10 31 0.3× 85 1.0× 85 1.0× 42 0.9× 54 1.2× 50 325
Jiansen Zhao China 8 55 0.6× 59 0.7× 46 0.6× 37 0.8× 73 1.6× 21 366

Countries citing papers authored by F. Hooshmand

Since Specialization
Citations

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

Fields of papers citing papers by F. Hooshmand

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of F. Hooshmand

This figure shows the co-authorship network connecting the top 25 collaborators of F. Hooshmand. A scholar is included among the top collaborators of F. Hooshmand 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 F. Hooshmand. F. Hooshmand 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.
Hooshmand, F., et al.. (2025). A novel extension of SVM model with piecewise linear penalty function. Progress in Artificial Intelligence. 14(3). 319–340.
2.
Hooshmand, F., et al.. (2025). A novel convex-hull-based algorithm for classification problems with imbalanced and overlapping data. Expert Systems with Applications. 298. 129691–129691.
3.
MirHassani, S.​A., et al.. (2025). Fractional Programming-Based Heuristic: An Efficient Method for Marine Inventory Routing Problem. Operations Research Forum. 6(2).
4.
MirHassani, S.​A., et al.. (2024). A modelling and solution approach for wind-affected drone-truck routing problem under uncertainty. Expert Systems with Applications. 257. 124996–124996. 9 indexed citations
5.
Hooshmand, F.. (2024). Stochastic optimization models for the solar system design and energy management problem in an off-grid residential house. Journal of Energy Storage. 100. 113615–113615. 2 indexed citations
6.
Bayat, Maryam, F. Hooshmand, & S.​A. MirHassani. (2024). Scenario-based stochastic model and efficient cross-entropy algorithm for the risk-budgeting problem. Annals of Operations Research. 341(2-3). 731–755. 1 indexed citations
7.
Bayat, M., F. Hooshmand, & S.​A. MirHassani. (2024). Drawdown minimization in asset portfolio selection: MINLP models and efficient cross‐entropy algorithm. International Transactions in Operational Research. 33(3). 1806–1830.
8.
Hooshmand, F., et al.. (2024). Adjustable robust optimization approach for SVM under uncertainty. Omega. 131. 103206–103206. 2 indexed citations
9.
MirHassani, S.​A., et al.. (2023). Handling the significance of regression coefficients via optimization. Expert Systems with Applications. 238. 121910–121910. 1 indexed citations
10.
Hooshmand, F., et al.. (2023). A novel stochastic programming model under endogenous uncertainty for the CCS-EOR planning problem. Applied Energy. 338. 120605–120605. 3 indexed citations
11.
Hooshmand, F., et al.. (2023). Enhanced index tracking problem: a new optimization model and a sum-of-ratio based algorithm. OPSEARCH. 60(3). 1286–1311. 1 indexed citations
12.
Hooshmand, F., et al.. (2023). A sensor location model and an efficient GA for the traffic volume estimation. Soft Computing. 28(4). 2987–3013. 1 indexed citations
13.
Hooshmand, F., et al.. (2023). Model and efficient algorithm for the portfolio selection problem with real‐world constraints under value‐at‐risk measure. International Transactions in Operational Research. 30(5). 2665–2690. 7 indexed citations
14.
MirHassani, S.​A., et al.. (2022). Modeling and solution algorithm for a disaster management problem based on Benders decomposition. IISE Transactions. 54(12). 1161–1171. 2 indexed citations
15.
MirHassani, S.​A., et al.. (2020). Solving two-dimensional cutting stock problem via a DNA computing algorithm. Natural Computing. 20(1). 145–159. 6 indexed citations
16.
Hooshmand, F., et al.. (2020). Risk-Based Models for Optimal Sensor Location Problems in Water Networks. Journal of Water Resources Planning and Management. 146(11). 7 indexed citations
17.
Hooshmand, F., et al.. (2019). Logic-based benders decomposition algorithm for contamination detection problem in water networks. Computers & Operations Research. 115. 104840–104840. 11 indexed citations
18.
Hooshmand, F., et al.. (2018). Adapting GA to solve a novel model for operating room scheduling problem with endogenous uncertainty. Operations Research for Health Care. 19. 26–43. 22 indexed citations
19.
MirHassani, S.​A., et al.. (2017). Model and algorithm for bi-fuel vehicle routing problem to reduce GHG emissions. Environmental Science and Pollution Research. 24(27). 21610–21624. 17 indexed citations
20.
Hooshmand, F. & S.​A. MirHassani. (2017). Reduction of nonanticipativity constraints in multistage stochastic programming problems with endogenous and exogenous uncertainty. Mathematical Methods of Operations Research. 87(1). 1–18. 8 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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