Oliver Schütze

3.5k total citations · 1 hit paper
86 papers, 2.0k citations indexed

About

Oliver Schütze is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Oliver Schütze has authored 86 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Computational Theory and Mathematics, 37 papers in Artificial Intelligence and 19 papers in Statistics, Probability and Uncertainty. Recurrent topics in Oliver Schütze's work include Advanced Multi-Objective Optimization Algorithms (60 papers), Metaheuristic Optimization Algorithms Research (35 papers) and Probabilistic and Robust Engineering Design (19 papers). Oliver Schütze is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (60 papers), Metaheuristic Optimization Algorithms Research (35 papers) and Probabilistic and Robust Engineering Design (19 papers). Oliver Schütze collaborates with scholars based in Mexico, United States and Germany. Oliver Schütze's co-authors include Carlos A. Coello Coello, Adriana Lara, Michael Dellnitz, Jian‐Qiao Sun, Carlos Hernández, Gustavo Sánchez, El‐Ghazali Talbi, Furui Xiong, Massimiliano Vasile and Marco Laumanns and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Applied Mechanics and International Journal of Computer Vision.

In The Last Decade

Oliver Schütze

86 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization

2012 361 citations Oliver Schütze, Adriana Lara et al. IEEE Transactions on Evolutionary Computation profile →

Peers

Oliver Schütze

CTM

CSE

SPU

MSOR

Qie He United States

Anne Auger France

Luc Jaulin France

Chaoli Sun China

Natalia Alexandrov United States

Paul D. Frank United States

Hemant Kumar Singh Australia

Ilan Kroo United States

B.E. Stuckman United States

Ryoji Tanabe Japan

Qie He United States

Oliver Schütze

1.2k ×0.9

CTM

1.6k ×1.5

225 ×0.6

CSE

56 ×0.2

SPU

113 ×0.5

MSOR

Citations per year, relative to Oliver Schütze Oliver Schütze (= 1×) peers Qie He

Countries citing papers authored by Oliver Schütze

Since Specialization

Citations

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

Fields of papers citing papers by Oliver Schütze

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Oliver Schütze

This figure shows the co-authorship network connecting the top 25 collaborators of Oliver Schütze. A scholar is included among the top collaborators of Oliver Schütze 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 Oliver Schütze. Oliver Schütze 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

Hernández, Carlos, et al.. (2024). Finding ϵ-Locally Optimal Solutions for Multiobjective Multimodal Optimization. IEEE Transactions on Evolutionary Computation. 29(5). 2019–2031. 4 indexed citations

Quiróz-Castellanos, Marcela, Luis Gerardo de la Fraga, Adriana Lara, Leonardo Trujillo, & Oliver Schütze. (2023). Numerical and Evolutionary Optimization 2021. Mathematical and Computational Applications. 28(3). 71–71. 1 indexed citations

Wang, Hao, et al.. (2023). The Hypervolume Newton Method for Constrained Multi-Objective Optimization Problems. Mathematical and Computational Applications. 28(1). 10–10. 1 indexed citations

Coello, Carlos A. Coello, Erik D. Goodman, Kaisa Miettinen, et al.. (2023). Interview: Kalyanmoy Deb Talks about Formation, Development and Challenges of the EMO Community, Important Positions in His Career, and Issues Faced Getting His Works Published. Mathematical and Computational Applications. 28(2). 34–34. 5 indexed citations

Hernández, Carlos & Oliver Schütze. (2022). A bounded archive based for bi-objective problems based on distance and e-dominance to avoid cyclic behavior. Proceedings of the Genetic and Evolutionary Computation Conference. 583–591. 2 indexed citations

Schütze, Oliver, et al.. (2020). Pareto Explorer for Solving Real World Applications. Research in computing science. 149. 29–36. 1 indexed citations

Lara, Adriana, et al.. (2020). Dataset on a Benchmark for Equality Constrained Multi-objective Optimization. SHILAP Revista de lepidopterología. 29. 105130–105130. 4 indexed citations

Schütze, Oliver, et al.. (2019). Pareto Explorer: a global/local exploration tool for many-objective optimization problems. Engineering Optimization. 52(5). 832–855. 26 indexed citations

Schütze, Oliver, et al.. (2019). A neural network-evolutionary computational framework for remaining useful life estimation of mechanical systems. Neural Networks. 116. 178–187. 42 indexed citations

10.

Trujillo, Leonardo, et al.. (2018). Numerical and Evolutionary Optimization – NEO 2017. Studies in computational intelligence. 2 indexed citations

11.

Bogoya, Manuel, et al.. (2018). A (p,q)-Averaged Hausdorff Distance for Arbitrary Measurable Sets. Mathematical and Computational Applications. 23(3). 51–51. 21 indexed citations

12.

Roblin, Patrick, et al.. (2017). Comparison of a genetic programming approach with ANFIS for power amplifier behavioral modeling and FPGA implementation. Soft Computing. 23(7). 2463–2481. 8 indexed citations

13.

Maldonado, Yazmín, et al.. (2016). Optimizing the location of ambulances in Tijuana, Mexico. Computers in Biology and Medicine. 80. 107–115. 42 indexed citations

14.

Schütze, Oliver, et al.. (2015). Solving the ambulance location problem in Tijuana-Mexico using a continuous location model. 2631–2638. 2 indexed citations

15.

Xiong, Furui, Oliver Schütze, Qian Ding, & Jian‐Qiao Sun. (2015). Finding zeros of nonlinear functions using the hybrid parallel cell mapping method. Communications in Nonlinear Science and Numerical Simulation. 34. 23–37. 15 indexed citations

16.

Rudolph, Günter, Heike Trautmann, & Oliver Schütze. (2012). Homogene Approximation der Paretofront bei mehrkriteriellen Kontrollproblemen. at - Automatisierungstechnik. 60(10). 612–621. 3 indexed citations

17.

Lara, Adriana, Carlos A. Coello Coello, & Oliver Schütze. (2010). A painless gradient-assisted multi-objective memetic mechanism for solving continuous bi-objective optimization problems. 1–8. 7 indexed citations

18.

Schütze, Oliver, et al.. (2010). Computing Gap Free Pareto Front Approximations with Stochastic Search Algorithms. Evolutionary Computation. 18(1). 65–96. 43 indexed citations

19.

Schütze, Oliver, El‐Ghazali Talbi, Gregorio Toscano‐Pulido, Carlos A. Coello Coello, & Luis V. Santana‐Quintero. (2007). A Memetic PSO Algorithm for Scalar Optimization Problems. 128–134. 15 indexed citations

20.

Dellnitz, Michael, Oliver Schütze, & Qinghua Zheng. (2002). Locating all the zeros of an analytic function in one complex variable. Journal of Computational and Applied Mathematics. 138(2). 325–333. 45 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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