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Computer Science

D-Index
64
Citations
20293
World Ranking
2555
National Ranking
146

Overview

Jürgen Branke is affiliated with the University of Warwick in the United Kingdom, focusing primarily on computer science research. Their work spans various subfields including artificial intelligence, computational theory and mathematics, management science and operations research, industrial and manufacturing engineering, and control and systems engineering.

The scientist has contributed extensively to multiple topics within their research domain. Key areas of focus include:

  • Advanced Multi-Objective Optimization Algorithms
  • Machine Learning and Data Classification
  • Metaheuristic Optimization Algorithms Research
  • Simulation Techniques and Applications
  • Gaussian Processes and Bayesian Inference
  • Optimal Experimental Design Methods
  • Evolutionary Algorithms and Applications

Jürgen Branke's recent published papers cover a range of subjects relevant to machine learning, optimization, and operational research. Notable papers include:

  • "Multi-Objective Hyperparameter Optimization in Machine Learning-An Overview" (2023) published in ACM Transactions on Evolutionary Learning and Optimization
  • "Ranking and selection for pairwise comparison" (2023) published in Naval Research Logistics (NRL)
  • "Dynamic multi-period vehicle routing with touting" (2023) published in European Journal of Operational Research
  • "Bayesian Optimization" (2024) published in Proceedings of the Genetic and Evolutionary Computation Conference Companion
  • "Multi-objective optimisation of multifaceted maintenance strategies for wind farms" (2022) published in Journal of the Operational Research Society

The venues in which Jürgen Branke frequently publishes include:

  • arXiv (Cornell University)
  • Proceedings of the Genetic and Evolutionary Computation Conference Companion
  • European Journal of Operational Research
  • ACM Transactions on Evolutionary Learning and Optimization
  • IEEE Transactions on Evolutionary Computation

Collaboration is a consistent feature of their research, with frequent co-authors including:

  • Sebastian Rojas Gonzalez
  • Juan Ungredda
  • Ivo Couckuyt
  • Danial Yazdani
  • Linda Wanika

Jürgen Branke's contributions focus on computational methods to enhance optimization and machine learning processes, integrating theoretical and applied research methodologies.

Best Publications

  • Evolutionary optimization in uncertain environments-a survey

    Yaochu Jin;J. Branke

  • Multiobjective Optimization: Interactive and Evolutionary Approaches

    Jürgen Branke;Kalyanmoy Deb;Kaisa Miettinen;Roman Słowiński

  • Evolutionary Optimization in Dynamic Environments

    Jurgen Branke

  • Memory enhanced evolutionary algorithms for changing optimization problems

    J. Branke

  • Evolutionary dynamic optimization: A survey of the state of the art

    Trung Thanh Nguyen;Shengxiang Yang;Juergen Branke

  • Finding Knees in Multi-objective Optimization

    Jürgen Branke;Kalyanmoy Deb;Henning Dierolf;Matthias Osswald

  • Multiswarms, exclusion, and anti-convergence in dynamic environments

    T. Blackwell;J. Branke

  • A Multi-population Approach to Dynamic Optimization Problems

    Jürgen Branke;Thomas Kaussler;Christian Smidt;Hartmut Schmeck

  • Multi-swarm Optimization in Dynamic Environments

    Tim Blackwell;Jürgen Branke

  • Automated Design of Production Scheduling Heuristics: A Review

    Jurgen Branke;Su Nguyen;Christoph W. Pickardt;Mengjie Zhang

  • Guidance in evolutionary multi-objective optimization

    J Branke;T Kaußler;H Schmeck

  • Selecting a Selection Procedure

    Jürgen Branke;Stephen E. Chick;Christian Schmidt

  • Creating Robust Solutions by Means of Evolutionary Algorithms

    Jürgen Branke

  • Reliability-Based Optimization Using Evolutionary Algorithms

    K. Deb;S. Gupta;D. Daum;J. Branke

  • Designing evolutionary algorithms for dynamic optimization problems

    Jürgen Branke;Hartmut Schmeck

  • Portfolio optimization with an envelope-based multi-objective evolutionary algorithm

    Jürgen Branke;Benedikt Scheckenbach;Michael Stein;Kalyan Deb

  • Towards a generic observer/controller architecture for Organic Computing.

    Urban Richter;Moez Mnif;Jürgen Branke;Christian Müller-Schloer

  • Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation

    I. Paenke;J. Branke;Yaochu Jin

  • Faster convergence by means of fitness estimation

    J. Branke;C. Schmidt

  • Ant Colony Optimization.

    Jürgen Branke;Michael Guntsch

  • Applications of Evolutionary Computing - EvoWorkshops 2004: EvoBio, EvoComNet, EvoHOT, EvoIASP, EvoMUSART, EvoSTOC, Coimbra, Portugal

    Günther R. Raidl;Stefano Cagnoni;Jürgen Branke;David Wolfe Corne

Frequent Co-Authors

Hartmut Schmeck
Hartmut Schmeck Karlsruhe Institute of Technology
Kalyanmoy Deb
Kalyanmoy Deb Michigan State University
Yaochu Jin
Yaochu Jin Westlake University
Rolf Drechsler
Rolf Drechsler University of Bremen
Xiaodong Li
Xiaodong Li University of Virginia
Roman Słowiński
Roman Słowiński Poznań University of Technology
Kaisa Miettinen
Kaisa Miettinen University of Jyväskylä
Hussein A. Abbass
Hussein A. Abbass University of New South Wales
Salvatore Greco
Salvatore Greco University of Portsmouth

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