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Computer Science

D-Index
36
Citations
7050
World Ranking
11100
National Ranking
556

Overview

Günter Rudolph is affiliated with TU Dortmund University in Germany and conducts research primarily at the intersection of computer science, medicine, and biochemistry, genetics, and molecular biology. Their work spans multiple fields, notably computational theory and mathematics, artificial intelligence, molecular biology, genetics, and computer vision and pattern recognition.

Their research focuses on several key topics, including advanced multi-objective optimization algorithms, metaheuristic optimization algorithms research, music technology and sound studies, music and audio processing, corneal surgery and disorders, advanced control systems optimization, and scheduling and optimization algorithms.

Recent published papers by Günter Rudolph include:

  • Diagnosis of Inherited Retinal Diseases, 2021, Klinische Monatsblätter für Augenheilkunde
  • Gene Therapy for Inherited Retinal Disorders: Update on Clinical Trials, 2021, Klinische Monatsblätter für Augenheilkunde
  • Vitamin B12 in Leber hereditary optic neuropathy mutation carriers: a prospective cohort study, 2022, Orphanet Journal of Rare Diseases
  • Evolutionary composition of music with learned melody evaluation, 2022, Publikationen an der Universität Bielefeld (Universität Bielefeld)
  • Benchmark-Driven Configuration of a Parallel Model-Based Optimization Algorithm, 2022, IEEE Transactions on Evolutionary Computation

Günter Rudolph frequently publishes in venues such as Klinische Monatsblätter für Augenheilkunde, arXiv (Cornell University), Publikationen an der Universität Bielefeld (Universität Bielefeld), Orphanet Journal of Rare Diseases, and Molecular Genetics & Genomic Medicine.

The scientist has contributed to book publications with Springer Science+Business Media, including two editions of Parallel Problem Solving from Nature - PPSN XVII published in 2022.

Frequent collaborators include Anna V. Kononova, Claudia Priglinger, Siegfried Priglinger, Igor Vatolkin, and Benjamin Doerr, each having coauthored multiple publications with Günter Rudolph.

Best Publications

  • Exploratory landscape analysis

    Olaf Mersmann;Bernd Bischl;Heike Trautmann;Mike Preuss

  • Convergence properties of some multi-objective evolutionary algorithms

    G. Rudolph;A. Agapie

  • Parallel Problem Solving from Nature – PPSN X

    Günter Rudolph;Thomas Jansen;Nicola Beume;Simon Lucas

  • Finite Markov chain results in evolutionary computation: a tour d'horizon

    Günter Rudolph

  • Contemporary Evolution Strategies

    Hans-Paul Schwefel;Günter Rudolph

  • A Spatial Predator-Prey Approach to Multi-objective Optimization: A Preliminary Study

    Marco Laumanns;Günter Rudolph;Hans-Paul Schwefel

  • Convergence of evolutionary algorithms in general search spaces

    G. Rudolph

  • On a multi-objective evolutionary algorithm and its convergence to the Pareto set

    G. Rudolph

  • Proceedings of the Genetic and Evolutionary Computation Conference

    William B. Langdon;Erick Cantú-Paz;Keith E. Mathias;Rajkumar Roy

  • Parallel Problem Solving from Nature - PPSN XI

    Robert Schaefer;Carlos Cotta;Joanna Kołodziej;Günter Rudolph

  • Local convergence rates of simple evolutionary algorithms with Cauchy mutations

    G. Rudolph

  • An Evolutionary Algorithm for Integer Programming

    Günter Rudolph

  • Self-adaptive mutations may lead to premature convergence

    G. Rudolph

  • Capabilities of EMOA to detect and preserve equivalent pareto subsets

    Günter Rudolph;Boris Naujoks;Mike Preuss

  • How mutation and selection solve long-path problems in polynomial expected time

    Günter Rudolph

  • Theory of evolutionary algorithms: a bird's eye view

    A. E. Eiben;G. Rudolph

  • Parallel Approaches for Multiobjective Optimization

    El-Ghazali Talbi;Sanaz Mostaghim;Tatsuya Okabe;Hisao Ishibuchi

  • Pareto set and EMOA behavior for simple multimodal multiobjective functions

    Mike Preuss;Boris Naujoks;Günter Rudolph

  • Faster s-metric calculation by considering dominated hypervolume as klee's measure problem.

    Nicola Beume;Günter Rudolph

  • Evolutionary Search under Partially Ordered Fitness Sets

    Günter Rudolph

  • GECCO 2002: Proceedings of the genetic and evolutionary computation conference

    W.B. Langdon;E. Cant{ 'u}-Paz;K. Mathias;R. Roy

  • Parallel problem solving from nature - PPSN X : 10th international conference, Dortmund, Germany, September 13-17, 2008 : proceedings

    Günter Rudolph;Thomas Jansen;Simon M Lucas;Carlo Poloni

Frequent Co-Authors

Mike Preuss
Mike Preuss Leiden University
Heike Trautmann
Heike Trautmann University of Münster
Bernd Bischl
Bernd Bischl Ludwig-Maximilians-Universität München
Kathrin Klamroth
Kathrin Klamroth University of Wuppertal
Thomas Jansen
Thomas Jansen Aberystwyth University
Xin Yao
Xin Yao Lingnan University
Marco Laumanns
Marco Laumanns ZF Friedrichshafen (Germany)
Simon M. Lucas
Simon M. Lucas Queen Mary University of London
Joshua Knowles
Joshua Knowles University of Manchester
Christian Igel
Christian Igel University of Copenhagen

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