Manlio Gaudioso

2.2k total citations
85 papers, 1.5k citations indexed

About

Manlio Gaudioso is a scholar working on Numerical Analysis, Computational Theory and Mathematics and Computational Mechanics. According to data from OpenAlex, Manlio Gaudioso has authored 85 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Numerical Analysis, 29 papers in Computational Theory and Mathematics and 24 papers in Computational Mechanics. Recurrent topics in Manlio Gaudioso's work include Advanced Optimization Algorithms Research (35 papers), Optimization and Variational Analysis (21 papers) and Sparse and Compressive Sensing Techniques (20 papers). Manlio Gaudioso is often cited by papers focused on Advanced Optimization Algorithms Research (35 papers), Optimization and Variational Analysis (21 papers) and Sparse and Compressive Sensing Techniques (20 papers). Manlio Gaudioso collaborates with scholars based in Italy, France and Russia. Manlio Gaudioso's co-authors include Annabella Astorino, Antonio Fuduli, Giovanni Giallombardo, Jean‐François Cordeau, Luigi Moccia, Gilbert Laporte, Giovanna Miglionico, Giuseppe Paletta, Maria Flavia Monaco and Raffaele Cerulli and has published in prestigious journals such as European Journal of Operational Research, Sensors and IEEE Transactions on Neural Networks and Learning Systems.

In The Last Decade

Manlio Gaudioso

81 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Manlio Gaudioso Italy 23 537 427 423 303 284 85 1.5k
Louis Caccetta Australia 24 254 0.5× 472 1.1× 223 0.5× 109 0.4× 129 0.5× 111 1.8k
Richard V. Helgason United States 13 315 0.6× 232 0.5× 210 0.5× 72 0.2× 109 0.4× 21 1.3k
Tobias Achterberg Germany 13 586 1.1× 528 1.2× 355 0.8× 284 0.9× 35 0.1× 25 1.8k
Julius Žilinskas Lithuania 20 86 0.2× 564 1.3× 461 1.1× 410 1.4× 75 0.3× 89 1.2k
Panagiotis Patrinos Belgium 22 150 0.3× 226 0.5× 336 0.8× 265 0.9× 263 0.9× 118 2.0k
Qie He United States 10 272 0.5× 1.2k 2.7× 119 0.3× 1.6k 5.1× 32 0.1× 18 2.1k
Marc E. Pfetsch Germany 17 283 0.5× 240 0.6× 127 0.3× 55 0.2× 217 0.8× 74 1.2k
Guy Cohen France 22 287 0.5× 1.5k 3.6× 357 0.8× 125 0.4× 128 0.5× 95 2.7k
Faiz Al-Khayyal United States 16 362 0.7× 405 0.9× 476 1.1× 61 0.2× 69 0.2× 32 1.3k
Pietro Belotti United States 15 172 0.3× 362 0.8× 360 0.9× 103 0.3× 62 0.2× 40 1.3k

Countries citing papers authored by Manlio Gaudioso

Since Specialization
Citations

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

Fields of papers citing papers by Manlio Gaudioso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Manlio Gaudioso

This figure shows the co-authorship network connecting the top 25 collaborators of Manlio Gaudioso. A scholar is included among the top collaborators of Manlio Gaudioso 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 Manlio Gaudioso. Manlio Gaudioso 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.
Gaudioso, Manlio, Giovanni Giallombardo, & Giovanna Miglionico. (2023). Sparse optimization via vector k-norm and DC programming with an application to feature selection for support vector machines. Computational Optimization and Applications. 86(2). 745–766. 5 indexed citations
2.
Gaudioso, Manlio, Giampaolo Liuzzi, & Stefano Lucidi. (2023). A clustering heuristic to improve a derivative-free algorithm for nonsmooth optimization. Optimization Letters. 18(1). 57–71. 1 indexed citations
3.
D’Alessandro, Pietro, Manlio Gaudioso, Giovanni Giallombardo, & Giovanna Miglionico. (2023). The Descent–Ascent Algorithm for DC Programming. INFORMS journal on computing. 36(2). 657–671. 1 indexed citations
4.
Gaudioso, Manlio, Giovanni Giallombardo, & Jean‐Baptiste Hiriart‐Urruty. (2023). Dual formulation of the sparsity constrained optimization problem: application to classification. Optimization methods & software. 39(1). 84–101. 1 indexed citations
5.
Gaudioso, Manlio, et al.. (2023). New mixed integer fractional programming problem and some multi-objective models for sparse optimization. Soft Computing. 27(21). 15893–15904. 2 indexed citations
6.
Gaudioso, Manlio, Sona Taheri, Adil Bagirov, & Napsu Karmitsa. (2023). Bundle Enrichment Method for Nonsmooth Difference of Convex Programming Problems. Algorithms. 16(8). 394–394.
7.
Gaudioso, Manlio, Giovanni Giallombardo, & Giovanna Miglionico. (2022). Essentials of numerical nonsmooth optimization. Annals of Operations Research. 314(1). 213–253. 3 indexed citations
8.
Carrabs, Francesco & Manlio Gaudioso. (2020). A Lagrangian approach for the minimum spanning tree problem with conflicting edge pairs. Networks. 78(1). 32–45. 11 indexed citations
9.
Gaudioso, Manlio, Giovanni Giallombardo, & Giovanna Miglionico. (2019). Essentials of numerical nonsmooth optimization. 4OR. 18(1). 1–47. 8 indexed citations
10.
Astorino, Annabella, Antonio Fuduli, & Manlio Gaudioso. (2019). A Lagrangian Relaxation Approach for Binary Multiple Instance Classification. IEEE Transactions on Neural Networks and Learning Systems. 30(9). 2662–2671. 27 indexed citations
11.
Gaudioso, Manlio, Giovanni Giallombardo, Giovanna Miglionico, & Eugenio Vocaturo. (2019). Classification in the multiple instance learning framework via spherical separation. Soft Computing. 24(7). 5071–5077. 25 indexed citations
12.
Gaudioso, Manlio, Giovanni Giallombardo, & Giovanna Miglionico. (2018). A savings-based model for two-shipper cooperative routing. Optimization Letters. 12(8). 1811–1824. 2 indexed citations
13.
Gaudioso, Manlio, Giovanni Giallombardo, & Marat S. Mukhametzhanov. (2017). Numerical infinitesimals in a variable metric method for convex nonsmooth optimization. Applied Mathematics and Computation. 318. 312–320. 21 indexed citations
14.
Gaudioso, Manlio, Giovanni Giallombardo, Giovanna Miglionico, & Adil Bagirov. (2017). Minimizing nonsmooth DC functions via successive DC piecewise-affine approximations. Journal of Global Optimization. 71(1). 37–55. 41 indexed citations
15.
Gaudioso, Manlio, Giovanni Giallombardo, & Giovanna Miglionico. (2017). Minimizing Piecewise-Concave Functions Over Polyhedra. Mathematics of Operations Research. 43(2). 580–597. 14 indexed citations
16.
Gaudioso, Manlio, et al.. (2017). Lagrangian relaxation for SVM feature selection. Computers & Operations Research. 87. 137–145. 40 indexed citations
17.
Karmitsa, Napsu, et al.. (2017). Diagonal bundle method with convex and concave updates for large-scale nonconvex and nonsmooth optimization. Optimization methods & software. 34(2). 363–382. 1 indexed citations
18.
Gaudioso, Manlio, et al.. (2007). On the Use of the SVM Approach in Analyzing an Electronic Nose. 42–46. 4 indexed citations
19.
Cordeau, Jean‐François, Manlio Gaudioso, Gilbert Laporte, & Luigi Moccia. (2006). A Memetic Heuristic for the Generalized Quadratic Assignment Problem. INFORMS journal on computing. 18(4). 433–443. 39 indexed citations
20.
Gaudioso, Manlio & Giuseppe Paletta. (1992). A Heuristic for the Periodic Vehicle Routing Problem. Transportation Science. 26(2). 86–92. 92 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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