J. Branke

发表

Sanjoy Dasgupta, Hannu Toivonen, Pieter Abbeel, 2020, Encyclopedia of Machine Learning.

Sanjoy Dasgupta, Hannu Toivonen, Pieter Abbeel, 2010, Encyclopedia of Machine Learning and Data Mining.

Organic Computing – Addressing Complexity by Controlled Self-Organization

Hartmut Schmeck, Christian Müller-Schloer, Jürgen Branke, 2006, Second International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (isola 2006).

Guidance in evolutionary multi-objective optimization

J. Branke, H. Schmeck, T. Kaußler, 2001 .

Dynamic Graph Drawing

Jürgen Branke, J. Branke, 2001, Drawing Graphs.

Multiobjective optimization for dynamic environments

Hussein A. Abbass, Jürgen Branke, Lam Thu Bui, 2005, 2005 IEEE Congress on Evolutionary Computation.

Multiobjective optimization

Kalyanmoy Deb, Kaisa Miettinen, Roman Słowiński, 1997 .

Evolutionary generation of dispatching rule sets for complex dynamic scheduling problems

Bernd Scholz-Reiter, Jürgen Branke, Christoph W. Pickardt, 2013 .

Reducing the sampling variance when searching for robust solutions

J. Branke, 2001 .

Measurement and Control of Self-organised Behaviour in Robot Swarms

Hartmut Schmeck, Christian Müller-Schloer, Jürgen Branke, 2007, ARCS.

Generating dispatching rules for semiconductor manufacturing to minimize weighted tardiness

Bernd Scholz-Reiter, Jürgen Branke, Christoph W. Pickardt, 2010, Proceedings of the 2010 Winter Simulation Conference.

Applications of Evolutionary Computing

Rolf Drechsler, Franz Rothlauf, Elena Marchiori, 2004, Lecture Notes in Computer Science.

GECCO 2007: Genetic and Evolutionary Computation Conference

Thomas Stützle, Riccardo Poli, Mauro Birattari, 2007 .

Constraint handling in efficient global optimization

Kalyanmoy Deb, Jürgen Branke, Jonathan E. Fieldsend, 2017, GECCO.

Solving the Probabilistic TSP with Ant Colony Optimization

Jürgen Branke, Michael Guntsch, J. Branke, 2004 .

Reliability-based optimization for multiple constraints with evolutionary algorithms

Kalyanmoy Deb, Jürgen Branke, David A. Daum, 2007, 2007 IEEE Congress on Evolutionary Computation.

New Sampling Strategies When Searching for Robust Solutions

Jürgen Branke, Xin Fei, Nalân Gülpınar, 2019, IEEE Transactions on Evolutionary Computation.

Learning Model-Ensemble Policies with Genetic Programming

J. Branke, T. Bartz-Beielstein, Oliver Flasch, 2015 .

Constraint Handling in E icient Global Optimization

J. Branke, Samineh Bagheri, K. Sindhya, 2017 .

Interactive evolutionary multiobjective optimization driven by robust ordinal regression

J. Branke, S. Greco, R. Słowiński, 2010 .

The Role of Representations in Dynamic Knapsack Problems

Jürgen Branke, A. Sima Etaner-Uyar, Merve Orbayi, 2006, EvoWorkshops.

Robust Optimization Over Time by Learning Problem Space Characteristics

Jürgen Branke, Trung Thanh Nguyen, Danial Yazdani, 2019, IEEE Transactions on Evolutionary Computation.

ACTUATED TRAFFIC SIGNAL OPTIMIZATION USING EVOLUTIONARY ALGORITHMS

J. Branke, Holger Prothmann, Peter Goldate, 2007 .

Portfolio Selection: How to Integrate Complex Constraints

J. Branke, H. Schmeck, Michael Stein, 2022 .

Simulation optimisation: tutorial

Jürgen Branke, J. Branke, 2018, Annual Conference on Genetic and Evolutionary Computation.

A Unified View on Metaheuristics and Their Hybridization

Jürgen Branke, Hartmut Schmeck, Michael Stein, 2005, Handbook of Bioinspired Algorithms and Applications.

Approximate Dynamic Programming

Geoffrey I. Webb, Stephen Grossberg, Mauro Birattari, 2011 .

A Survey of Evolutionary Continuous Dynamic Optimization Over Two Decades—Part A

J. Branke, Yaochu Jin, X. Yao, 2021, IEEE Transactions on Evolutionary Computation.

Robust Optimization Over Time by Estimating Robustness of Promising Regions

J. Branke, A. Gandomi, Xin Yao, 2023, IEEE Transactions on Evolutionary Computation.

Practical Approaches to Multi-Objective Optimization

Kalyanmoy Deb, Jürgen Branke, Kaisa Miettinen, 2005 .

Guest Editorial Special Issue on Evolutionary Computation in the Presence of Uncertainty

Jürgen Branke, Yaochu Jin, J. Branke, 2006 .

Multiobjective Ranking and Selection Using Stochastic Kriging

J. Branke, I. Nieuwenhuyse, Sebastian Rojas-Gonzalez, 2022, ArXiv.

2 Traditional Approach to Interactive Analysis with the Use of Single Objective Metaheuristics

J. Branke, A. Jaszkiewicz, 2008 .

Proceedings of the Workshop on Evolutionary Algorithms for Dynamic Optimization Problems (EvoDOP-2003) held in conjunction with the Genetic and Evolutionary Computation Conference (GECCO-2003), 12 July 2003, Chicago, USA [online]

Jürgen Branke, J. Branke, 2003 .

09041 Working Group on EMO for Robust Multiobjective Optimization (1st Round)

Nirupam Chakraborti, Nicola Beume, Kalyanmoy Deb, 2009, Hybrid and Robust Approaches to Multiobjective Optimization.

Self-Organised Routing for Road Networks

Jörg Hähner, Hartmut Schmeck, Christian Müller-Schloer, 2012, IWSOS.

Applications of Evolutionary Computing: Evoworkshops: EvoBIO, EvoCOMNET, EvoHot, EvoIASP, EvoMUSART, and EvoSTOC (Lecture Notes in Computer Science)

Rolf Drechsler, Franz Rothlauf, Elena Marchiori, 2005 .

Spirostanol glycoside from the tuber of Ophiopogon japonicus

J. Branke, E. Haslinger, 1995 .

Hyper-heuristic Evolution of Dispatching Rules: A Comparison of Rule Representations

Bernd Scholz-Reiter, Jürgen Branke, Torsten Hildebrandt, 2015, Evolutionary Computation.

Theoretical Analysis of Simple Evolution Strategies in Quickly Changing Environments

Wei Wang, Jürgen Branke, J. Branke, 2003, GECCO.

Evolutionary algorithms for dynamic optimization problems: workshop preface

Shengxiang Yang, Jürgen Branke, J. Branke, 2005, GECCO '05.

Multi-swarm Optimization in Dynamic Environments

Jürgen Branke, Tim Blackwell, J. Branke, 2004, EvoWorkshops.

A feasible role of sulfate-reducing bacteria in the termite gut

J. Branke, H. König, H. Cypionka, 1996 .

A Survey of Evolutionary Continuous Dynamic Optimization Over Two Decades—Part B

J. Branke, Yaochu Jin, Ran Cheng, 2021, IEEE Transactions on Evolutionary Computation.

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

Shengxiang Yang, Jürgen Branke, Trung Thanh Nguyen, 2012, Swarm Evol. Comput..

Evolutionary Design of Emergent Behavior

Jürgen Branke, Hartmut Schmeck, J. Branke, 2008, Organic Computing.

Integrating Techniques from Statistical Ranking into Evolutionary Algorithms

Jürgen Branke, Stephen E. Chick, Christian Schmidt, 2006, EvoWorkshops.

Selection in the Presence of Noise

Jürgen Branke, Christian Schmidt, J. Branke, 2003, GECCO.

Psychrotolerant sulfate-reducing bacteria from an oxic freshwater sediment, description of Desulfovibrio cuneatus sp. nov. and Desulfovibrio litoralis sp. nov.

J. Branke, H. König, H. Cypionka, 1998, Systematic and applied microbiology.

16S-like rDNA sequence and phylogenetic position of the diplomonad Spironucleus muris (Lavier 1936)

J. Branke, H. König, J. Reimann, 1996 .

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

Jürgen Branke, Yaochu Jin, Ingo Paenke, 2006, IEEE Transactions on Evolutionary Computation.

Faster convergence by means of fitness estimation

Jürgen Branke, Christian Schmidt, J. Branke, 2005, Soft Comput..

Efficient fitness estimation in noisy environments

Jürgen Branke, Hartmut Schmeck, Christian Schmidt, 2001 .

Sequential sampling for noisy optimisation with CMA-ES

Jürgen Branke, Matthew J. Groves, J. Branke, 2018, GECCO.

Balancing Population- and Individual-Level Adaptation in Changing Environments

Jürgen Branke, Yaochu Jin, Ingo Paenke, 2009, Adapt. Behav..

Evolutionary optimization in uncertain environments-a survey

Jürgen Branke, Yaochu Jin, J. Branke, 2005, IEEE Transactions on Evolutionary Computation.

Designing evolutionary algorithms for dynamic optimization problems

Hartmut Schmeck, Jürgen Branke, J. Branke, 2003 .

Anticipation in Dynamic Optimization: The Scheduling Case

Jürgen Branke, Dirk C. Mattfeld, J. Branke, 2000, PPSN.

Evolutionary Optimization in Dynamic Environments

Jürgen Branke, J. Branke, 2001, Genetic Algorithms and Evolutionary Computation.

Top-κ selection with pairwise comparisons

Jürgen Branke, Matthew J. Groves, J. Branke, 2019, Eur. J. Oper. Res..

Sequential Sampling to Myopically Maximize the Expected Value of Information

Jürgen Branke, Stephen E. Chick, Christian Schmidt, 2010, INFORMS J. Comput..

Efficient pairwise preference elicitation allowing for indifference

Jürgen Branke, Salvatore Greco, Salvatore Corrente, 2017, Comput. Oper. Res..

Using Choquet integral as preference model in interactive evolutionary multiobjective optimization

Jürgen Branke, Salvatore Greco, Salvatore Corrente, 2016, Eur. J. Oper. Res..

Parallel Problem Solving from Nature – PPSN XIII

Thomas Bartz-Beielstein, Jürgen Branke, Jim Smith, 2014, Lecture Notes in Computer Science.

Empirical comparison of MOPSO methods - Guide selection and diversity preservation -

Jürgen Branke, Sanaz Mostaghim, Nikhil Padhye, 2009, 2009 IEEE Congress on Evolutionary Computation.

On performance metrics and particle swarm methods for dynamic multiobjective optimization problems

Xiaodong Li, Jürgen Branke, Michael Kirley, 2007, 2007 IEEE Congress on Evolutionary Computation.

Performance measures and particle swarm methods for dynamic multi-objective optimization problems

Xiaodong Li, Jürgen Branke, Michael Kirley, 2007, GECCO '07.

Survey: State of the Art

Jürgen Branke, J. Branke, 2002 .

Consideration of Partial User Preferences in Evolutionary Multiobjective Optimization

Jürgen Branke, J. Branke, 2008, Multiobjective Optimization.

Learning Value Functions in Interactive Evolutionary Multiobjective Optimization

Jürgen Branke, Salvatore Greco, Roman Slowinski, 2015, IEEE Transactions on Evolutionary Computation.

Distribution of Evolutionary Algorithms in Heterogeneous Networks

Jürgen Branke, Hartmut Schmeck, Andreas Kamper, 2004, GECCO.

Reducing Genetic Drift in Steady State Evolutionary Algorithms

Jürgen Branke, Massimo Cutaia, Heinrich Dold, 1999, Annual Conference on Genetic and Evolutionary Computation.

Addressing sampling errors and diversity loss in UMDA

Jürgen Branke, Jonathan L. Shapiro, Clemens Lode, 2007, GECCO '07.

Worst-case robustness and a related decision support

Jürgen Branke, Gideon Avigad, J. Branke, 2008, Annual Conference on Genetic and Evolutionary Computation.

New Approaches to Coevolutionary Worst-Case Optimization

Jürgen Branke, Johanna Rosenbusch, J. Branke, 2008, PPSN.

Optimal Sampling for Simulated Annealing Under Noise

Jürgen Branke, Stephan Meisel, Robin C. Ball, 2018, INFORMS J. Comput..

Meta-optimization for parameter tuning with a flexible computing budget

Jürgen Branke, Jawad Elomari, J. Branke, 2012, GECCO '12.

Simulated annealing in the presence of noise

Jürgen Branke, Stephan Meisel, Christian Schmidt, 2008, J. Heuristics.

Selecting a Selection Procedure

Jürgen Branke, Stephen E. Chick, Christian Schmidt, 2007, Manag. Sci..

Evolutionary design of en-route caching strategies

Jürgen Branke, Pablo Funes, Frederik Thiele, 2007, Appl. Soft Comput..

Evolving En-Route Caching Strategies for the Internet

Jürgen Branke, Pablo Funes, Frederik Thiele, 2004, GECCO.

Ant Colony Optimization

Jürgen Branke, Michael Guntsch, J. Branke, 2005, Handbook of Bioinspired Algorithms and Applications.

Simulation optimisation: tutorial

Jürgen Branke, J. Branke, 2019, Annual Conference on Genetic and Evolutionary Computation.

Reference Point-Based Particle Swarm Optimization Using a Steady-State Approach

Xiaodong Li, Jürgen Branke, Richard Allmendinger, 2008, SEAL.

Finding Knees in Multi-objective Optimization

Kalyanmoy Deb, Jürgen Branke, Henning Dierolf, 2004, PPSN.

About Selecting the Personal Best in Multi-Objective Particle Swarm Optimization

Jürgen Branke, Sanaz Mostaghim, J. Branke, 2006, PPSN.

Proceedings of the 3rd European conference on Applications of Evolutionary Computing

Rolf Drechsler, Franz Rothlauf, Jürgen Branke, 2005 .

Artificial Societies

Jürgen Branke, J. Branke, 2010, Encyclopedia of Machine Learning.

Artificial Intelligence in Asset Management

Jürgen Branke, Söhnke M. Bartram, Söhnke M. Bartram, 2019, SSRN Electronic Journal.

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

Kalyanmoy Deb, Jürgen Branke, Hartmut Schmeck, 2009, Eur. J. Oper. Res..

Simulation Optimisation: Tutorial

Jürgen Branke, J. Branke, 2016, Annual Conference on Genetic and Evolutionary Computation.

Dynamic scheduling of multi-product continuous biopharmaceutical facilities: A hyper-heuristic framework

Jürgen Branke, Suzanne S. Farid, Richard Allmendinger, 2019, Comput. Chem. Eng..

Efficient solution selection for two-stage stochastic programs

Nalan Gülpinar, Jürgen Branke, Xin Fei, 2019, Eur. J. Oper. Res..

New greedy myopic and existing asymptotic sequential selection procedures: preliminary empirical results

Jürgen Branke, Stephen E. Chick, Christian Schmidt, 2007, 2007 Winter Simulation Conference.

A Multi-population Approach to Dynamic Optimization Problems

Jürgen Branke, Hartmut Schmeck, Thomas Kaussler, 2000 .

Evolutionary Algorithms

Thomas Bartz-Beielstein, Jürgen Branke, Olaf Mersmann, 2014, WIREs Data Mining Knowl. Discov..

Interactive Evolutionary Multiobjective Optimization Using Robust Ordinal Regression

Jürgen Branke, Salvatore Greco, Roman Slowinski, 2009, EMO.

Algorithms for the multi-objective vehicle routing problem with hard time windows and stochastic travel time and service time

Jürgen Branke, Douglas Moura Miranda, Samuel Vieira Conceição, 2018, Appl. Soft Comput..

A Distributed Genetic Algorithm Improving the Generalization Behavior of Neural Networks

Hartmut Schmeck, Jürgen Branke, Udo Kohlmorgen, 1995, ECML.

Multi-objective particle swarm optimization on computer grids

Jürgen Branke, Sanaz Mostaghim, Hartmut Schmeck, 2007, GECCO '07.

Parallelizing multi-objective evolutionary algorithms: cone separation

Kalyanmoy Deb, Jürgen Branke, Hartmut Schmeck, 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

Identifying Stochastically Non-dominated Solutions Using Evolutionary Computation

J. Branke, Hemant K. Singh, 2022, PPSN.

On Using Surrogates with Genetic Programming

Jürgen Branke, Torsten Hildebrandt, J. Branke, 2015, Evolutionary Computation.

Evolutionary synthesis of multi-agent systems for dynamic dial-a-ride problems

Tom Holvoet, Jürgen Branke, Greet Vanden Berghe, 2012, GECCO '12.

Evolutionary algorithms and multi-objectivization for the travelling salesman problem

Xiaodong Li, Jürgen Branke, Martin Jähne, 2009, GECCO.

Sequential Sampling in Noisy Environments

Jürgen Branke, Christian Schmidt, J. Branke, 2004, PPSN.

Multi-objective worst case optimization by means of evolutionary algorithms

Jürgen Branke, Gideon Avigad, Amiram Moshaiov, 2013 .

Reliability-Based Optimization Using Evolutionary Algorithms

Kalyanmoy Deb, Jürgen Branke, Shubham Gupta, 2009, IEEE Transactions on Evolutionary Computation.

Improving the Scalability of EA Techniques: A Case Study in Clustering

Jürgen Branke, A. Sima Etaner-Uyar, Stefan R. Bach, 2009, Artificial Evolution.

A new lot sizing and scheduling heuristic for multi-site biopharmaceutical production

Suzanne S. Farid, Jürgen Branke, Richard Allmendinger, 2017, J. Heuristics.

Interactive Multiobjective Evolutionary Algorithms

Jürgen Branke, Andrzej Jaszkiewicz, J. Branke, 2008, Multiobjective Optimization.

Response Surfaces with Discounted Information for Global Optima Tracking in Dynamic Environments

Jürgen Branke, Sergio Morales-Enciso, J. Branke, 2013, NICSO.

Particle Swarms for Dynamic Optimization Problems

Xiaodong Li, Jürgen Branke, Tim Blackwell, 2008, Swarm Intelligence.

Multiswarms, exclusion, and anti-convergence in dynamic environments

Jürgen Branke, Tim Blackwell, J. Branke, 2006, IEEE Transactions on Evolutionary Computation.

Optimization in Dynamic Environments

Jürgen Branke, J. Branke, 2002 .

Memory enhanced evolutionary algorithms for changing optimization problems

Jürgen Branke, J. Branke, 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

Particle swarm with speciation and adaptation in a dynamic environment

Xiaodong Li, Jürgen Branke, Tim Blackwell, 2006, GECCO.

Benchmarking Continuous Dynamic Optimization: Survey and Generalized Test Suite

Ran Cheng, Trung Thanh Nguyen, Xin Yao, 2020, IEEE Transactions on Cybernetics.

Scaling Up Dynamic Optimization Problems: A Divide-and-Conquer Approach

Xin Yao, Jürgen Branke, Trung Thanh Nguyen, 2020, IEEE Transactions on Evolutionary Computation.

Interactive Multiobjective Optimization from a Learning Perspective

Jürgen Branke, Valerie Belton, Salvatore Greco, 2008, Multiobjective Optimization.

Efficient implementation of an active set algorithm for large-scale portfolio selection

Jürgen Branke, Hartmut Schmeck, Michael Stein, 2008, Comput. Oper. Res..

Finding the Trade-off between Robustness and Worst-case Quality

Ke Lu, Jürgen Branke, J. Branke, 2015, GECCO.

Creating Robust Solutions by Means of Evolutionary Algorithms

Jürgen Branke, J. Branke, 1998, PPSN.

Towards an analysis of dynamic environments

A. Sima Etaner-Uyar, Jürgen Branke, Erdem Salihoglu, 2005, GECCO '05.

A New Multi-swarm Particle Swarm Optimization for Robust Optimization Over Time

Jin Wang, Jürgen Branke, Trung Thanh Nguyen, 2017, EvoApplications.

Asynchronous multiple objective particle swarm optimisation in unreliable distributed environments

Andrew Lewis, Jürgen Branke, Sanaz Mostaghim, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Automated Design of Production Scheduling Heuristics: A Review

Mengjie Zhang, Jürgen Branke, Su Nguyen, 2016, IEEE Transactions on Evolutionary Computation.

Optimizing agents with genetic programming: an evaluation of hyper-heuristics in dynamic real-time logistics

Tom Holvoet, Jürgen Branke, Rinde R. S. van Lon, 2018, Genetic Programming and Evolvable Machines.

Setup-oriented dispatching rules – a survey

Jürgen Branke, Christoph W. Pickardt, J. Branke, 2012 .

Evolving control rules for a dual-constrained job scheduling scenario

Jürgen Branke, Torsten Hildebrandt, Matthew J. Groves, 2016, 2016 Winter Simulation Conference (WSC).

Changing or keeping solutions in dynamic optimization problems with switching costs

Xin Yao, Jürgen Branke, Trung Thanh Nguyen, 2018, GECCO.

A Multi-objective Time-Linkage Approach for Dynamic Optimization Problems with Previous-Solution Displacement Restriction

Jin Wang, Jürgen Branke, Trung Thanh Nguyen, 2018, EvoApplications.

Using Indifference Information in Robust Ordinal Regression

Jürgen Branke, Salvatore Greco, Salvatore Corrente, 2015, EMO.

An Improved Genetic Programming Hyper-Heuristic for the Uncertain Capacitated Arc Routing Problem

Yi Mei, Mengjie Zhang, Jürgen Branke, 2018, Australasian Conference on Artificial Intelligence.

Formulations and algorithms for the multi-path selection problem in network routing

Jürgen Branke, Arie M. C. A. Koster, Nayyar Almas Kazmi, 2012, 2012 IV International Congress on Ultra Modern Telecommunications and Control Systems.

Efficient expected improvement estimation for continuous multiple ranking and selection

Jürgen Branke, Michael Pearce, J. Branke, 2017, 2017 Winter Simulation Conference (WSC).

Experimental Analysis of Bound Handling Techniques in Particle Swarm Optimization

Jürgen Branke, Sanaz Mostaghim, Sabine Helwig, 2013, IEEE Transactions on Evolutionary Computation.

Efficient Evolutionary Algorithms for Searching Robust Solutions

Jürgen Branke, J. Branke, 2000 .

Multi-Objective Zero-Sum Games with Postponed Objective Preferences

Jürgen Branke, Gideon Avigad, Erella Eisenstadt, 2015 .

Continuous multi-task Bayesian Optimisation with correlation

Jürgen Branke, Michael Pearce, J. Branke, 2018, Eur. J. Oper. Res..

Waiting Strategies for Dynamic Vehicle Routing

Jürgen Branke, Martin Middendorf, Maged M. Dessouky, 2005, Transp. Sci..

Dynamic adjustment of dispatching rule parameters in flow shops with sequence-dependent set-up times

Jürgen Branke, Bernd Scholz-Reiter, Torsten Hildebrandt, 2016 .

Heuristics for the stochastic dynamic task-resource allocation problem with retry opportunities

Nalan Gülpinar, Jürgen Branke, Ethem Çanakoglu, 2018, Eur. J. Oper. Res..

ON PARALLELIZING MULTI-TASK BAYESIAN OPTIMIZATION

Jürgen Branke, Michael Pearce, Matthew J. Groves, 2018, 2018 Winter Simulation Conference (WSC).

Machine Learning for Active Portfolio Management

Giuliano De Rossi, Söhnke M. Bartram, J. Branke, 2021, The Journal of Financial Data Science.

Robustness Estimation and Optimisation for Semantic Web Service Composition With Stochastic Service Failures

J. Branke, Sven Hartmann, Chen Wang, 2022, IEEE Transactions on Emerging Topics in Computational Intelligence.

Parallel multi-objective optimization using Master-Slave model on heterogeneous resources

Andrew Lewis, Jürgen Branke, Sanaz Mostaghim, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Bayesian simulation optimization with input uncertainty

Jürgen Branke, Michael Pearce, J. Branke, 2017, 2017 Winter Simulation Conference (WSC).

Multiobjectivization with NSGA-II on the Noiseless BBOB Testbed

J. Branke, H. Abbass, T. Meyarivan, 2013 .

Multiobjective Ranking and Selection with Correlation and Heteroscedastic Noise

Inneke Van Nieuwenhuyse, Sebastian Rojas-Gonzalez, Jürgen Branke, 2019, 2019 Winter Simulation Conference (WSC).

On the Influence of Phenotype Plasticity on Genotype Diversity

Jürgen Branke, Yaochu Jin, Ingo Paenke, 2007, 2007 IEEE Symposium on Foundations of Computational Intelligence.

Task Scheduling Under Gang Constraints

Jürgen Branke, Dirk C. Mattfeld, J. Branke, 2005 .

Design of Gate Array Circuits Using Evolutionary Algorithms

Jürgen Branke, Sanaz Mostaghim, Hartmut Schmeck, 2008, ARCS.