J. G. Ecker

1.3k total citations
40 papers, 872 citations indexed

About

J. G. Ecker is a scholar working on Numerical Analysis, Control and Systems Engineering and Computational Theory and Mathematics. According to data from OpenAlex, J. G. Ecker has authored 40 papers receiving a total of 872 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Numerical Analysis, 19 papers in Control and Systems Engineering and 17 papers in Computational Theory and Mathematics. Recurrent topics in J. G. Ecker's work include Advanced Optimization Algorithms Research (24 papers), Optimization and Mathematical Programming (12 papers) and Optimization and Variational Analysis (6 papers). J. G. Ecker is often cited by papers focused on Advanced Optimization Algorithms Research (24 papers), Optimization and Mathematical Programming (12 papers) and Optimization and Variational Analysis (6 papers). J. G. Ecker collaborates with scholars based in United States, Belgium and Niger. J. G. Ecker's co-authors include Elmor L. Peterson, Jun‐Yeob Song, J. Regis McNamara, William E. Boyce, Robert A. Leitch, Mark Cecchini, William A. Wallace, Shimon Awerbuch, Yves Smeers and Xiao Cheng and has published in prestigious journals such as Management Science, Water Resources Research and European Journal of Operational Research.

In The Last Decade

J. G. Ecker

39 papers receiving 780 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. G. Ecker United States	16	442	410	399	148	85	40	872
J. J. H. Forrest United States	11	191 0.4×	246 0.6×	216 0.5×	70 0.5×	85 1.0×	16	670
Faiz Al-Khayyal United States	16	416 0.9×	476 1.2×	405 1.0×	86 0.6×	101 1.2×	32	1.3k
Nicolas W. Sawaya United States	7	380 0.9×	221 0.5×	160 0.4×	66 0.4×	152 1.8×	7	778
Timo Berthold Germany	16	276 0.6×	318 0.8×	319 0.8×	154 1.0×	126 1.5×	44	968
Stefan Vigerske Germany	14	226 0.5×	150 0.4×	148 0.4×	78 0.5×	148 1.7×	31	582
Joseph Czyzyk United States	6	122 0.3×	120 0.3×	120 0.3×	78 0.5×	112 1.3×	7	564
Cihan H. Tuncbilek United States	7	162 0.4×	297 0.7×	232 0.6×	32 0.2×	60 0.7×	7	553
U. Passy Israel	11	156 0.4×	203 0.5×	197 0.5×	120 0.8×	25 0.3×	37	604
C. M. Shetty United States	14	196 0.4×	265 0.6×	280 0.7×	78 0.5×	14 0.2×	36	664
Jordi Castro Spain	14	84 0.2×	193 0.5×	193 0.5×	59 0.4×	58 0.7×	52	543

Countries citing papers authored by J. G. Ecker

Since Specialization

Citations

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

Fields of papers citing papers by J. G. Ecker

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. G. Ecker

This figure shows the co-authorship network connecting the top 25 collaborators of J. G. Ecker. A scholar is included among the top collaborators of J. G. Ecker 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 J. G. Ecker. J. G. Ecker 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

Ecker, J. G., et al.. (2008). Solving Bilevel Linear Programs Using Multiple Objective Linear Programming. Journal of Optimization Theory and Applications. 140(2). 197–212. 19 indexed citations

Ecker, J. G., et al.. (2002). An application of nonlinear optimization in molecular biology. European Journal of Operational Research. 138(2). 452–458. 9 indexed citations

Ecker, J. G., et al.. (2002). Active set strategies and an ellipsoid algorithm for general nonlinear programming problems. 1 indexed citations

Boyce, William E. & J. G. Ecker. (1995). The Computer-oriented Calculus Course at Rensselaer Polytechnic Institute. College Mathematics Journal. 26(1). 45–50. 6 indexed citations

Boyce, William E. & J. G. Ecker. (1995). The Computer-Oriented Calculus Course at Rensselaer Polytechnic Institute. College Mathematics Journal. 26(1). 45–45. 8 indexed citations

Ecker, J. G. & Jun‐Yeob Song. (1994). Optimizing a linear function over an efficient set. Journal of Optimization Theory and Applications. 83(3). 541–563. 39 indexed citations

Ecker, J. G., et al.. (1994). Performance of Several Optimization Methods on Robot Trajectory Planning Problems. SIAM Journal on Scientific Computing. 15(6). 1401–1412. 3 indexed citations

Ecker, J. G., et al.. (1988). Introduction to operations research. Medical Entomology and Zoology. 8 indexed citations

Ecker, J. G., et al.. (1984). Comparison of a special-purpose algorithm with general-purpose algorithms for solving geometric programming problems. Journal of Optimization Theory and Applications. 43(2). 237–263. 6 indexed citations

10.

Ecker, J. G., et al.. (1984). A class of rank-two ellipsoid algorithms for convex programming. Mathematical Programming. 29(2). 187–202. 4 indexed citations

11.

Ecker, J. G.. (1981). Postoptimal analyses, parametric programming, and related topics. European Journal of Operational Research. 6(1). 85–86. 30 indexed citations

12.

Ecker, J. G., et al.. (1978). COMPUTATIONAL ASPECTS OF GEOMETRIC PROGRAMMING 3. SOME PRIMAL AND DUAL ALGORITHMS FOR POSYNOMIAL AND SIGNOMIAL GEOMETRIC PROGRAMS. Engineering Optimization. 3(3). 147–160. 1 indexed citations

13.

Ecker, J. G., et al.. (1978). Optimal design of a dry-type natural-draft cooling tower by geometric programming. Journal of Optimization Theory and Applications. 26(2). 305–323. 8 indexed citations

14.

Ecker, J. G., et al.. (1976). An Easy Primal Method for Geometric Programming. Management Science. 23(1). 71–77. 8 indexed citations

15.

Ecker, J. G.. (1975). A Geometric Programming Model for Optimal Allocation of Stream Dissolved Oxygen. Management Science. 21(6). 658–668. 29 indexed citations

16.

Ecker, J. G.. (1972). Decomposition in separable geometric programming. Journal of Optimization Theory and Applications. 9(3). 176–186. 2 indexed citations

17.

Peterson, Elmor L. & J. G. Ecker. (1970). Geometric programming: Duality in quadratic programming and lp-approximation III (degenerate programs). Journal of Mathematical Analysis and Applications. 29(2). 365–383. 22 indexed citations

18.

Peterson, Elmor L. & J. G. Ecker. (1969). Geometric Programming: Duality in Quadratic Programming and $l_p $-Approximation II (Canonical Programs). SIAM Journal on Applied Mathematics. 17(2). 317–340. 19 indexed citations

19.

Peterson, Elmor L. & J. G. Ecker. (1968). Geometric programming: A unified duality theory for quadratically constrained quadratic programs and 𝑙_{𝑝}-constrained 𝑙_{𝑝}-approximation problems. Bulletin of the American Mathematical Society. 74(2). 316–321. 6 indexed citations

20.

Ecker, J. G.. (1968). Geometric Programming: Duality In Quadratic Programming And 'l'(,p)-approximation.. Deep Blue (University of Michigan). 2 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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