Jacques Gauvin

1.0k total citations
11 papers, 498 citations indexed

About

Jacques Gauvin is a scholar working on Computational Theory and Mathematics, Numerical Analysis and Control and Systems Engineering. According to data from OpenAlex, Jacques Gauvin has authored 11 papers receiving a total of 498 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computational Theory and Mathematics, 7 papers in Numerical Analysis and 4 papers in Control and Systems Engineering. Recurrent topics in Jacques Gauvin's work include Optimization and Variational Analysis (10 papers), Advanced Optimization Algorithms Research (6 papers) and Optimization and Mathematical Programming (4 papers). Jacques Gauvin is often cited by papers focused on Optimization and Variational Analysis (10 papers), Advanced Optimization Algorithms Research (6 papers) and Optimization and Mathematical Programming (4 papers). Jacques Gauvin collaborates with scholars based in Canada and France. Jacques Gauvin's co-authors include Gilles Savard and Jon W. Tolle and has published in prestigious journals such as Mathematical Programming, SIAM Journal on Control and Optimization and Annals of Operations Research.

In The Last Decade

Jacques Gauvin

11 papers receiving 429 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jacques Gauvin Canada	7	377	292	164	66	47	11	498
S. Zlobec Canada	15	423 1.1×	355 1.2×	174 1.1×	55 0.8×	69 1.5×	60	569
Laura Martein Italy	9	276 0.7×	243 0.8×	168 1.0×	28 0.4×	49 1.0×	32	480
Phan Thiên Thach Vietnam	10	290 0.8×	285 1.0×	92 0.6×	37 0.6×	44 0.9×	27	407
P. Loridan France	8	397 1.1×	198 0.7×	130 0.8×	70 1.1×	74 1.6×	17	489
Stan Fromovitz United States	3	343 0.9×	301 1.0×	139 0.8×	39 0.6×	41 0.9×	6	447
Alberto Cambini Italy	9	238 0.6×	197 0.7×	132 0.8×	24 0.4×	51 1.1×	20	427
B. Bank India	7	495 1.3×	336 1.2×	214 1.3×	133 2.0×	46 1.0×	12	743
Dingju Zhu China	10	314 0.8×	171 0.6×	117 0.7×	36 0.5×	47 1.0×	21	421
T.-H. Shiau United States	6	197 0.5×	156 0.5×	55 0.3×	47 0.7×	18 0.4×	10	350
Andreas Löhne Germany	14	363 1.0×	298 1.0×	99 0.6×	143 2.2×	25 0.5×	34	508

Countries citing papers authored by Jacques Gauvin

Since Specialization

Citations

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

Fields of papers citing papers by Jacques Gauvin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jacques Gauvin

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

All Works

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11 of 11 papers shown

1.

Gauvin, Jacques, et al.. (1999). Lipschitz-Type Stability in Nonsmooth Convex Programs. SIAM Journal on Control and Optimization. 38(1). 124–137. 5 indexed citations

2.

Savard, Gilles & Jacques Gauvin. (1994). The steepest descent direction for the nonlinear bilevel programming problem. Operations Research Letters. 15(5). 265–272. 121 indexed citations

3.

Savard, Gilles & Jacques Gauvin. (1990). The Steepest Descent Direction for the Nonlinear Bilevel Programming Problem. PolyPublie (École Polytechnique de Montréal). 1–15. 1 indexed citations

4.

Gauvin, Jacques, et al.. (1990). Directional derivative of the value function in parametric optimization. Annals of Operations Research. 27(1). 237–252. 12 indexed citations

5.

Gauvin, Jacques, et al.. (1989). Directional Lipschitzian Optimal Solutions and Directional Derivative for the Optimal Value Function in Nonlinear Mathematical Programming. Annales de l Institut Henri Poincaré C Analyse Non Linéaire. 6. 305–324. 5 indexed citations

6.

Gauvin, Jacques, et al.. (1988). Directional Behaviour of Optimal Solutions in Nonlinear Mathematical Programming. Mathematics of Operations Research. 13(4). 629–649. 50 indexed citations

7.

Gauvin, Jacques. (1980). Ouelques Precisions Sur Les Prix Marginaux En Programmation Lineaire^*. INFOR Information Systems and Operational Research. 18(1). 68–73. 5 indexed citations

8.

Gauvin, Jacques. (1980). Shadow prices in nonconvex mathematical programming. Mathematical Programming. 19(1). 300–312. 11 indexed citations

9.

Gauvin, Jacques. (1979). The Generalized Gradient of a Marginal Function in Mathematical Programming. Mathematics of Operations Research. 4(4). 458–463. 33 indexed citations

10.

Gauvin, Jacques. (1977). A necessary and sufficient regularity condition to have bounded multipliers in nonconvex programming. Mathematical Programming. 12(1). 136–138. 188 indexed citations

11.

Gauvin, Jacques & Jon W. Tolle. (1977). Differential Stability in Nonlinear Programming. SIAM Journal on Control and Optimization. 15(2). 294–311. 67 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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