M. J. Cánovas

822 total citations
57 papers, 516 citations indexed

About

M. J. Cánovas is a scholar working on Computational Theory and Mathematics, Numerical Analysis and Control and Systems Engineering. According to data from OpenAlex, M. J. Cánovas has authored 57 papers receiving a total of 516 indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Computational Theory and Mathematics, 52 papers in Numerical Analysis and 21 papers in Control and Systems Engineering. Recurrent topics in M. J. Cánovas's work include Optimization and Variational Analysis (54 papers), Advanced Optimization Algorithms Research (52 papers) and Advanced Control Systems Optimization (8 papers). M. J. Cánovas is often cited by papers focused on Optimization and Variational Analysis (54 papers), Advanced Optimization Algorithms Research (52 papers) and Advanced Control Systems Optimization (8 papers). M. J. Cánovas collaborates with scholars based in Spain, Australia and United States. M. J. Cánovas's co-authors include J. Parra, Marco A. López, F. Javier Toledo, M. I. Todorov, Asen L. Dontchev, Abderrahim Hantoute, Boris S. Mordukhovich, Diethard Klatte, R. Henrion and Michel Théra and has published in prestigious journals such as European Journal of Operational Research, Journal of Mathematical Analysis and Applications and Mathematical Programming.

In The Last Decade

M. J. Cánovas

51 papers receiving 479 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. J. Cánovas Spain	14	442	422	180	67	65	57	516
J. Parra Spain	15	520 1.2×	494 1.2×	221 1.2×	81 1.2×	76 1.2×	58	606
M. I. Todorov Spain	13	343 0.8×	323 0.8×	114 0.6×	59 0.9×	54 0.8×	44	418
N. Dinh Vietnam	15	670 1.5×	523 1.2×	162 0.9×	165 2.5×	25 0.4×	40	745
Daishi Kuroiwa Japan	13	629 1.4×	450 1.1×	84 0.5×	199 3.0×	25 0.4×	47	712
Elena Molho Italy	10	477 1.1×	377 0.9×	66 0.4×	65 1.0×	16 0.2×	20	508
Abderrahim Hantoute Chile	10	287 0.6×	186 0.4×	81 0.5×	54 0.8×	19 0.3×	49	354
S. Nobakhtian Iran	13	478 1.1×	366 0.9×	228 1.3×	57 0.9×	12 0.2×	51	515
Trúóng Xuân Dúc Hā Vietnam	11	515 1.2×	357 0.8×	81 0.5×	95 1.4×	8 0.1×	20	570
N. D. Yen Vietnam	16	728 1.6×	509 1.2×	123 0.7×	57 0.9×	13 0.2×	52	784
Sorin‐Mihai Grad Germany	12	497 1.1×	360 0.9×	80 0.4×	60 0.9×	8 0.1×	39	544

Countries citing papers authored by M. J. Cánovas

Since Specialization

Citations

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

Fields of papers citing papers by M. J. Cánovas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. J. Cánovas. 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 M. J. Cánovas. The network helps show where M. J. Cánovas may publish in the future.

Co-authorship network of co-authors of M. J. Cánovas

This figure shows the co-authorship network connecting the top 25 collaborators of M. J. Cánovas. A scholar is included among the top collaborators of M. J. Cánovas 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 M. J. Cánovas. M. J. Cánovas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Cánovas, M. J., et al.. (2024). Feasibility problems via paramonotone operators in a convex setting. Optimization. 73(10). 3055–3086. 1 indexed citations

Cánovas, M. J., et al.. (2022). From Calmness to Hoffman Constants for Linear Semi-infinite Inequality Systems. SIAM Journal on Optimization. 32(4). 2859–2878.

Cánovas, M. J. & J. Parra. (2022). Stability and Sensitivity of Uncertain Linear Programs. Set-Valued and Variational Analysis. 30(4). 1403–1421.

Cánovas, M. J., et al.. (2022). Robust and continuous metric subregularity for linear inequality systems. Computational Optimization and Applications. 86(3). 967–988.

Cánovas, M. J., et al.. (2022). Lipschitz upper semicontinuity in linear optimization via local directional convexity. Optimization. 72(8). 2091–2108.

Cánovas, M. J., et al.. (2021). Projection-Based Local and Global Lipschitz Moduli of the Optimal Value in Linear Programming. Journal of Optimization Theory and Applications. 193(1-3). 280–299.

Cánovas, M. J., et al.. (2021). Calmness of Linear Constraint Systems under Structured Perturbations with an Application to the Path-Following Scheme. Set-Valued and Variational Analysis. 29(4). 839–860. 1 indexed citations

Beer, Gerald, M. J. Cánovas, Marco A. López, & J. Parra. (2020). Lipschitz modulus of linear and convex inequality systems with the Hausdorff metric. Mathematical Programming. 189(1-2). 75–98. 3 indexed citations

Cánovas, M. J., Alexander Y. Kruger, Hoàng Xuân Phú, & Michel Théra. (2020). Marco A. López, a Pioneer of Continuous Optimization in Spain. Vietnam Journal of Mathematics. 48(2). 211–219. 1 indexed citations

10.

Cánovas, M. J., et al.. (2019). An approach to calmness of linear inequality systems from Farkas lemma. Optimization Letters. 13(2). 295–307. 2 indexed citations

11.

Cánovas, M. J., et al.. (2018). Calmness of the Optimal Value in Linear Programming. SIAM Journal on Optimization. 28(3). 2201–2221. 5 indexed citations

12.

Cánovas, M. J., et al.. (2018). Lipschitz Modulus of the Optimal Value in Linear Programming. Journal of Optimization Theory and Applications. 182(1). 133–152. 4 indexed citations

13.

Cánovas, M. J., J. Parra, Jan-J. Rückmann, & F. Javier Toledo. (2017). Point-Based Neighborhoods for Sharp Calmness Constants in Linear Programming. Set-Valued and Variational Analysis. 25(4). 757–772. 4 indexed citations

14.

Cánovas, M. J., R. Henrion, J. Parra, & F. Javier Toledo. (2015). Critical Objective Size and Calmness Modulus in Linear Programming. Set-Valued and Variational Analysis. 24(4). 565–579. 3 indexed citations

15.

Cánovas, M. J., Asen L. Dontchev, Marco A. López, & J. Parra. (2008). Isolated calmness of solution mappings in convex semi-infinite optimization. Journal of Mathematical Analysis and Applications. 350(2). 829–837. 7 indexed citations

16.

Cánovas, M. J., et al.. (2008). Regularity modulus of arbitrarily perturbed linear inequality systems. Journal of Mathematical Analysis and Applications. 343(1). 315–327. 17 indexed citations

17.

Cánovas, M. J., Marco A. López, & J. Parra. (2007). On the equivalence of parametric contexts for linear inequality systems. Journal of Computational and Applied Mathematics. 217(2). 448–456. 1 indexed citations

18.

Cánovas, M. J., Marco A. López, J. Parra, & F. Javier Toledo. (2006). Ill-posedness with respect to the solvability in linear optimization. Linear Algebra and its Applications. 416(2-3). 520–540. 16 indexed citations

19.

Cánovas, M. J., Marco A. López, & J. Parra. (2002). Upper Semicontinuity of the Feasible Set Mapping for Linear Inequality Systems. Set-Valued Analysis. 10(4). 361–378. 19 indexed citations

20.

Cánovas, M. J., Marco A. López, J. Parra, & M. I. Todorov. (2001). Solving Strategies and Well-Posedness in Linear Semi-Infinite Programming. Annals of Operations Research. 101(1-4). 171–190. 13 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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