Rüdiger Schultz

3.6k total citations
68 papers, 2.1k citations indexed

About

Rüdiger Schultz is a scholar working on Management Science and Operations Research, Control and Systems Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Rüdiger Schultz has authored 68 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Management Science and Operations Research, 21 papers in Control and Systems Engineering and 18 papers in Computational Theory and Mathematics. Recurrent topics in Rüdiger Schultz's work include Risk and Portfolio Optimization (40 papers), Optimization and Mathematical Programming (16 papers) and Electric Power System Optimization (16 papers). Rüdiger Schultz is often cited by papers focused on Risk and Portfolio Optimization (40 papers), Optimization and Mathematical Programming (16 papers) and Electric Power System Optimization (16 papers). Rüdiger Schultz collaborates with scholars based in Germany, Netherlands and United States. Rüdiger Schultz's co-authors include Werner Römisch, Maarten H. van der Vlerk, Leen Stougie, Ralf Gollmer, Matthias Nowak, E. Handschin, Martin Rumpf, Harald Neumann, Sergio Conti and Sebastian Engell and has published in prestigious journals such as Mathematical Programming, International Journal of Electrical Power & Energy Systems and Computers & Chemical Engineering.

In The Last Decade

Rüdiger Schultz

65 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rüdiger Schultz Germany 25 1.1k 706 493 352 317 68 2.1k
Suvrajeet Sen United States 28 1.3k 1.2× 1.0k 1.5× 569 1.2× 506 1.4× 319 1.0× 104 2.9k
Wolfram Wiesemann United Kingdom 23 1.4k 1.3× 807 1.1× 354 0.7× 257 0.7× 229 0.7× 56 2.4k
James Luedtke United States 22 865 0.8× 743 1.1× 427 0.9× 249 0.7× 296 0.9× 53 2.2k
A. L. Soyster United States 15 1.0k 0.9× 871 1.2× 377 0.8× 417 1.2× 327 1.0× 46 2.4k
Berç Rüstem United Kingdom 26 1.3k 1.2× 732 1.0× 271 0.5× 151 0.4× 490 1.5× 121 2.7k
Jitka Dupačová Czechia 18 967 0.9× 493 0.7× 438 0.9× 146 0.4× 160 0.5× 52 1.8k
Peter Kall Switzerland 11 593 0.5× 515 0.7× 150 0.3× 155 0.4× 205 0.6× 19 1.3k
Werner Römisch Germany 28 1.6k 1.4× 985 1.4× 2.0k 4.0× 259 0.7× 360 1.1× 81 4.1k
Andy Philpott New Zealand 28 645 0.6× 420 0.6× 1.3k 2.7× 169 0.5× 177 0.6× 85 2.3k
François Oustry France 7 770 0.7× 1.9k 2.7× 190 0.4× 111 0.3× 534 1.7× 12 3.0k

Countries citing papers authored by Rüdiger Schultz

Since Specialization
Citations

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

Fields of papers citing papers by Rüdiger Schultz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rüdiger Schultz

This figure shows the co-authorship network connecting the top 25 collaborators of Rüdiger Schultz. A scholar is included among the top collaborators of Rüdiger Schultz 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 Rüdiger Schultz. Rüdiger Schultz 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.
Gugat, Martin, et al.. (2020). Convexity and starshapedness of feasible sets in stationary flow networks. Networks and Heterogeneous Media. 15(2). 171–195. 3 indexed citations
2.
Morton, David P., et al.. (2018). The stochastic programming heritage of Maarten van der Vlerk. Computational Management Science. 15(3-4). 319–323. 1 indexed citations
3.
Gugat, Martin, et al.. (2016). Networks of pipelines for gas with nonconstant compressibility factor: stationary states. Computational and Applied Mathematics. 37(2). 1066–1097. 13 indexed citations
4.
Schultz, Rüdiger, et al.. (2015). Lipschitzian Properties and Stability of a Class of First-Order Stochastic Dominance Constraints. SIAM Journal on Optimization. 25(1). 396–415. 4 indexed citations
5.
Schultz, Rüdiger, et al.. (2009). An algorithm for stochastic programs with first-order dominance constraints induced by linear recourse. Discrete Applied Mathematics. 158(4). 291–297. 10 indexed citations
6.
Conti, Sergio, et al.. (2009). Shape Optimization Under Uncertainty—A Stochastic Programming Perspective. SIAM Journal on Optimization. 19(4). 1610–1632. 66 indexed citations
7.
Schultz, Rüdiger, et al.. (2008). Risk neutral and risk averse power optimization in electricity networks with dispersed generation. Mathematical Methods of Operations Research. 69(2). 353–367. 8 indexed citations
8.
Nowak, Matthias, et al.. (2005). A Stochastic Integer Programming Model for Incorporating Day-Ahead Trading of Electricity into Hydro-Thermal Unit Commitment. Optimization and Engineering. 6(2). 163–176. 61 indexed citations
9.
Schultz, Rüdiger, et al.. (2005). Conditional Value-at-Risk in Stochastic Programs with Mixed-Integer Recourse. Mathematical Programming. 105(2-3). 365–386. 129 indexed citations
10.
Schultz, Rüdiger, et al.. (2004). On deviation measures in stochastic integer programming. Operations Research Letters. 33(5). 441–449. 21 indexed citations
11.
Hemmecke, Raymond & Rüdiger Schultz. (2003). Decomposition of test sets in stochastic integer programming. Mathematical Programming. 94(2-3). 323–341. 24 indexed citations
12.
Schultz, Rüdiger, et al.. (2003). Risk Aversion via Excess Probabilities in Stochastic Programs with Mixed-Integer Recourse. SIAM Journal on Optimization. 14(1). 115–138. 63 indexed citations
13.
Engell, Sebastian, et al.. (2002). Scheduling of a multiproduct batch plant by two-stage stochastic integer programming. DuEPublico (University of Duisburg-Essen). 6 indexed citations
14.
Schultz, Rüdiger, Leen Stougie, & Maarten H. van der Vlerk. (1996). Two‐stage stochastic integer programming: a survey. Statistica Neerlandica. 50(3). 404–416. 75 indexed citations
15.
Schultz, Rüdiger. (1996). Rates of Convergence in Stochastic Programs with Complete Integer Recourse. SIAM Journal on Optimization. 6(4). 1138–1152. 30 indexed citations
16.
Schultz, Rüdiger, Leen Stougie, & Maarten H. van der Vlerk. (1995). Solving stochastic programs with integer recourse by enumeration : a framework using Gröbner basis reductions. TU/e Research Portal. 89(2). 279–81. 56 indexed citations
17.
Schultz, Rüdiger. (1994). Strong convexity in stochastic programs with complete recourse. Journal of Computational and Applied Mathematics. 56(1-2). 3–22. 16 indexed citations
18.
SZEMA, K., et al.. (1992). Application of a universe-series code for inviscid flow over complex3-dimensional configurations. 30th Aerospace Sciences Meeting and Exhibit. 1 indexed citations
19.
Römisch, Werner & Rüdiger Schultz. (1991). Distribution sensitivity in stochastic programming. Mathematical Programming. 50(1-3). 197–226. 49 indexed citations
20.
Schultz, Rüdiger. (1988). Estimates for Kuhn-Tucker points of perturbed convex programs. Optimization. 19(1). 29–43. 11 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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