Simone Sagratella

1.0k total citations
35 papers, 646 citations indexed

About

Simone Sagratella is a scholar working on Computational Theory and Mathematics, Numerical Analysis and Economics and Econometrics. According to data from OpenAlex, Simone Sagratella has authored 35 papers receiving a total of 646 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computational Theory and Mathematics, 13 papers in Numerical Analysis and 12 papers in Economics and Econometrics. Recurrent topics in Simone Sagratella's work include Optimization and Variational Analysis (20 papers), Advanced Optimization Algorithms Research (13 papers) and Economic theories and models (9 papers). Simone Sagratella is often cited by papers focused on Optimization and Variational Analysis (20 papers), Advanced Optimization Algorithms Research (13 papers) and Economic theories and models (9 papers). Simone Sagratella collaborates with scholars based in Italy, Germany and United States. Simone Sagratella's co-authors include Francisco Facchinei, Christian Kanzow, Gesualdo Scutari, Lorenzo Lampariello, Axel Dreves, Didier Aussel, Aviv Gibali, Yekini Shehu, Sebastian Karl and Oliver Stein and has published in prestigious journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and IEEE Transactions on Signal Processing.

In The Last Decade

Simone Sagratella

31 papers receiving 627 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Simone Sagratella Italy 14 312 202 151 131 101 35 646
Simai He United States 16 196 0.6× 177 0.9× 62 0.4× 157 1.2× 125 1.2× 44 809
Akiyoshi Shioura Japan 16 346 1.1× 82 0.4× 158 1.0× 192 1.5× 43 0.4× 69 758
Fabio Tardella Italy 17 216 0.7× 179 0.9× 137 0.9× 408 3.1× 37 0.4× 53 747
B. Bank India 7 495 1.6× 336 1.7× 67 0.4× 133 1.0× 74 0.7× 12 743
Jerzy Kyparisis United States 16 387 1.2× 268 1.3× 49 0.3× 150 1.1× 48 0.5× 23 810
Sebastian Pokutta United States 14 313 1.0× 104 0.5× 37 0.2× 50 0.4× 75 0.7× 83 701
Gui-Hua Lin China 16 508 1.6× 370 1.8× 68 0.5× 215 1.6× 71 0.7× 73 775
Georg Still Netherlands 17 753 2.4× 638 3.2× 56 0.4× 210 1.6× 121 1.2× 62 1.2k
Changjun Yu China 15 211 0.7× 220 1.1× 24 0.2× 136 1.0× 67 0.7× 67 801
Jan Outrata Czechia 16 773 2.5× 288 1.4× 43 0.3× 103 0.8× 40 0.4× 46 939

Countries citing papers authored by Simone Sagratella

Since Specialization
Citations

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

Fields of papers citing papers by Simone Sagratella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simone Sagratella

This figure shows the co-authorship network connecting the top 25 collaborators of Simone Sagratella. A scholar is included among the top collaborators of Simone Sagratella 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 Simone Sagratella. Simone Sagratella 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.
Lampariello, Lorenzo, et al.. (2025). Addressing Hierarchical Jointly Convex Generalized Nash Equilibrium Problems with Nonsmooth Payoffs. SIAM Journal on Optimization. 35(1). 445–475.
2.
Bigi, Giancarlo, et al.. (2023). Approximate variational inequalities and equilibria. Computational Management Science. 20(1). 1 indexed citations
3.
Cesarone, Francesco, et al.. (2023). A bilevel approach to ESG multi-portfolio selection. Computational Management Science. 20(1). 5 indexed citations
4.
Lampariello, Lorenzo, et al.. (2022). On the solution of monotone nested variational inequalities. Mathematical Methods of Operations Research. 96(3). 421–446. 4 indexed citations
5.
Lampariello, Lorenzo & Simone Sagratella. (2021). Effectively managing diagnostic tests to monitor the COVID-19 outbreak in Italy. Operations Research for Health Care. 28. 100287–100287. 7 indexed citations
6.
Lampariello, Lorenzo, et al.. (2021). Equilibrium selection for multi-portfolio optimization. European Journal of Operational Research. 295(1). 363–373. 9 indexed citations
7.
Lampariello, Lorenzo, et al.. (2020). An explicit Tikhonov algorithm for nested variational inequalities. Computational Optimization and Applications. 77(2). 335–350. 8 indexed citations
8.
Shehu, Yekini, Aviv Gibali, & Simone Sagratella. (2019). Inertial Projection-Type Methods for Solving Quasi-Variational Inequalities in Real Hilbert Spaces. Journal of Optimization Theory and Applications. 184(3). 877–894. 33 indexed citations
9.
Sagratella, Simone, et al.. (2019). The noncooperative fixed charge transportation problem. European Journal of Operational Research. 284(1). 373–382. 14 indexed citations
10.
Palagi, Laura, et al.. (2019). Case Article—Production and Distribution Optimization of Beach Equipment for the Marinero Company. INFORMS Transactions on Education. 19(3). 152–154.
11.
Lampariello, Lorenzo, Simone Sagratella, & Oliver Stein. (2019). The Standard Pessimistic Bilevel Problem. SIAM Journal on Optimization. 29(2). 1634–1656. 10 indexed citations
12.
Palagi, Laura, et al.. (2018). Parallel decomposition methods for linearly constrained problems subject to simple bound with application to the SVMs training. Computational Optimization and Applications. 71(1). 115–145. 7 indexed citations
13.
Sagratella, Simone. (2018). On generalized Nash equilibrium problems with linear coupling constraints and mixed-integer variables. Optimization. 68(1). 197–226. 18 indexed citations
14.
Sagratella, Simone, et al.. (2016). A convergent and fully distributable SVMs training algorithm. IRIS Research product catalog (Sapienza University of Rome). 12. 3076–3080. 7 indexed citations
15.
Facchinei, Francisco, Gesualdo Scutari, & Simone Sagratella. (2015). Parallel Selective Algorithms for Nonconvex Big Data Optimization. IEEE Transactions on Signal Processing. 63(7). 1874–1889. 106 indexed citations
16.
Facchinei, Francisco, Simone Sagratella, & Gesualdo Scutari. (2014). Parallel Algorithms for Big Data Optimization. arXiv (Cornell University). 4 indexed citations
17.
Facchinei, Francisco, Simone Sagratella, & Gesualdo Scutari. (2014). Flexible parallel algorithms for big data optimization. IRIS Research product catalog (Sapienza University of Rome). 7208–7212. 16 indexed citations
18.
Facchinei, Francisco, Christian Kanzow, & Simone Sagratella. (2013). Solving quasi-variational inequalities via their KKT conditions. Mathematical Programming. 144(1-2). 369–412. 87 indexed citations
19.
Santis, Alberto De, et al.. (2012). HIGH-RESOLUTION SAR IMAGES FOR FIRE SUSCEPTIBILITY ESTIMATION IN URBAN FORESTRY. SHILAP Revista de lepidopterología. XXXVIII-4/W19. 69–74. 1 indexed citations
20.
Santis, Alberto De, et al.. (2011). Integrating X-SAR images and anthropic factors for fire susceptibility assessment. IRIS Research product catalog (Sapienza University of Rome). 1. 818–821. 1 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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