Thomas Bäck

Thomas Bäck, Michael T. M. Emmerich, Kaifeng Yang, 2016, 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD).

Evolution strategies applied to perturbed objective functions

Thomas Bäck, Ulrich Hammel, Thomas Bäck, 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

A meta-genetic algorithm for solving the Capacitated Vehicle Routing Problem

Thomas Bäck, Michael T. M. Emmerich, Stefan Wink, 2012, 2012 IEEE Congress on Evolutionary Computation.

Mirrored orthogonal sampling with pairwise selection in evolution strategies

Hao Wang, Thomas Bäck, Michael T. M. Emmerich, 2014, SAC.

Mining a Chemical Database for Fragment Co-occurrence: Discovery of "Chemical Clichés"

Thomas Bäck, Joost N. Kok, Adriaan P. IJzerman, 2006, J. Chem. Inf. Model..

Optimizing Pedestrian Environments with Evolutionary Strategies

Thomas Bäck, Marijn Swenne, Thomas Bäck, 2014 .

Robust Parameter Settings for Variation Operators by Measuring the Resampling Ratio: A Study on Binary Constraint Satisfaction Problems

Jano I. van Hemert, Thomas Bäck, 2004, J. Heuristics.

Evolution Strategies on Noisy Functions: How to Improve Convergence Properties

Thomas Bäck, Ulrich Hammel, Thomas Bäck, 1994, PPSN.

Designoptimierung thermischer Trennverfahren mit memetischen Algorithmen und Aspen Plus Prozessmodellen

Thomas Bäck, Sebastian Engell, Maren Urselmann, 2015 .

Mixed Integer Evolution Strategies for Parameter Optimization

Thomas Bäck, Michael T. M. Emmerich, Johan H. C. Reiber, 2013, Evolutionary Computation.

Hyper-Parameter Optimization for Improving the Performance of Grammatical Evolution

Thomas Bäck, Hao Wang, Yitan Lou, 2019, 2019 IEEE Congress on Evolutionary Computation (CEC).

What is the value of your software?

Thomas Bäck, Joost Visser, Ariadi Nugroho, 2012, 2012 Third International Workshop on Managing Technical Debt (MTD).

Niching with derandomized evolution strategies in artificial and real-world landscapes

Ofer M. Shir, Thomas Bäck, Thomas Bäck, 2009, Natural Computing.

Evolutionary computation: an overview

Thomas Bäck, Hans-Paul Schwefel, H. Schwefel, 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

Academic education of software engineering practices: towards planning and improving capstone courses based upon intensive coaching and team routines

Thomas Bäck, Bernhard R. Katzy, Zhao Zhou, 2013, 2013 26th International Conference on Software Engineering Education and Training (CSEE&T).

An Overview of Evolutionary Algorithms for Parameter Optimization

Thomas Bäck, Hans-Paul Schwefel, H. Schwefel, 1993, Evolutionary Computation.

Niching in evolution strategies

Ofer M. Shir, Thomas Bäck, Thomas Bäck, 2005, GECCO '05.

Combining and Comparing Cluster Methods in a Receptor Database

Thomas Bäck, Joost N. Kok, Adriaan P. IJzerman, 2003, IDA.

Online selection of surrogate models for constrained black-box optimization

Thomas Bäck, Wolfgang Konen, Samineh Bagheri, 2016, 2016 IEEE Symposium Series on Computational Intelligence (SSCI).

Dynamic niching in evolution strategies with covariance matrix adaptation

Ofer M. Shir, Thomas Bäck, Thomas Bäck, 2005, 2005 IEEE Congress on Evolutionary Computation.

Towards an Adaptive CMA-ES Configurator

Thomas Bäck, Carola Doerr, Sander van Rijn, 2018, PPSN.

Optimally Weighted Cluster Kriging for Big Data Regression

Hao Wang, Thomas Bäck, Michael T. M. Emmerich, 2015, IDA.

Equality constraint handling for surrogate-assisted constrained optimization

Thomas Bäck, Wolfgang Konen, Samineh Bagheri, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Analysis and Visualization of Missing Value Patterns

Thomas Bäck, Wojtek Kowalczyk, Bas van Stein, 2016, IPMU.

A Reduced-Cost SMS-EMOA Using Kriging, Self-Adaptation, and Parallelization

Ofer M. Shir, Thomas Bäck, Michael T. M. Emmerich, 2008, MCDM.

Balancing risk and expected gain in kriging-based global optimization

Hao Wang, Thomas Bäck, Michael T. M. Emmerich, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Online anomaly detection on the webscope S5 dataset: A comparative study

Thomas Bäck, Wolfgang Konen, Markus Thill, 2017, 2017 Evolving and Adaptive Intelligent Systems (EAIS).

Compiling a benchmarking test-suite for combinatorial black-box optimization: a position paper

Ofer M. Shir, Thomas Bäck, Carola Doerr, 2018, GECCO.

RELIABILITY TEST DEMONSTRATION METHOD FOR EXPONENTIAL LIFE SYSTEM WITH RELIABILITY GROWTH UNDER THE CONDITION OF IN-TIME CORRECTIVE STRATEGY

Thomas Bäck, Michael Emmerich, Ping Jiang, 2016 .

Multi-criteria Airfoil Design with Evolution Strategies

Thomas Bäck, Lars Willmes, Thomas Bäck, 2003, EMO.

Measuring the Searched Space to Guide Efficiency: The Principle and Evidence on Constraint Satisfaction

Jano I. van Hemert, Thomas Bäck, 2002, PPSN.

Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1 + λ) EA variants on onemax and leadingones

Hao Wang, Thomas Bäck, Carola Doerr, 2018, GECCO.

Artificial Intelligence and Data Science in the Automotive Industry pdf

Thomas Bäck, Florian Neukart, Martin Hofmann, 2017, ArXiv.

Modeling user selection in quality diversity

Thomas Bäck, Alexander Asteroth, Alexander Hagg, 2019, GECCO.

Local subspace-based outlier detection using global neighbourhoods

Thomas Bäck, Bas van Stein, Matthijs van Leeuwen, 2016, 2016 IEEE International Conference on Big Data (Big Data).

Mirrored Orthogonal Sampling for Covariance Matrix Adaptation Evolution Strategies

Thomas Bäck, Michael Emmerich, Hao Wang, 2019, Evolutionary Computation.

Generalized Convergence Models for Tournament- and (mu, lambda)-Selection

Thomas Bäck, Thomas Bäck, 1995, ICGA.

Adaptive Niche Radii and Niche Shapes Approaches for Niching with the CMA-ES

Ofer M. Shir, Thomas Bäck, Michael T. M. Emmerich, 2010, Evolutionary Computation.

An analysis of the behavior of simplified evolutionary algorithms on trap functions

Thomas Bäck, Siegfried Nijssen, Thomas Bäck, 2003, IEEE Trans. Evol. Comput..

Using Genetic Algorithms to Evolve Behavior in Cellular Automata

Thomas Bäck, Ron Breukelaar, Thomas Bäck, 2005, UC.

Computing and the natural sciences at CiE 2005

Thomas Bäck, Benedikt Löwe, Thomas Bäck, 2007, Theor. Comput. Sci..

Reliable Hierarchical Clustering with the Self-organizing Map

Thomas Bäck, Joost N. Kok, Adriaan P. IJzerman, 2005, IDA.

The application of evolutionary multi-criteria optimization to dynamic molecular alignment

Ofer M. Shir, Thomas Bäck, Michael T. M. Emmerich, 2007, 2007 IEEE Congress on Evolutionary Computation.

Dynamic vehicle routing with time windows in theory and practice

Thomas Bäck, Michael T. M. Emmerich, Andries Stam, 2016, Natural Computing.

Sequential experimentation by evolutionary algorithms

Ofer M. Shir, Thomas Bäck, Thomas Bäck, 2019, GECCO.

Multi-point Efficient Global Optimization Using Niching Evolution Strategy

Hao Wang, Thomas Bäck, Michael T. M. Emmerich, 2015, EVOLVE.

Evolution strategies: basic introduction

Thomas Bäck, 2013, GECCO.

Refueling of a Nuclear Power Plant: Comparison of a Naive and a Specialized Mutation Operator

Cornelia Kappler, Thomas Bäck, Michele Zamparelli, 1996, PPSN.

Evolutionary Computation: A Guided Tour

Thomas Bäck, 2002, Bull. EATCS.

Substructure Mining Using Elaborate Chemical Representation

Thomas Bäck, Joost N. Kok, Siegfried Nijssen, 2006, J. Chem. Inf. Model..

Expected hypervolume improvement algorithm for PID controller tuning and the multiobjective dynamical control of a biogas plant

Thomas Bäck, Michael T. M. Emmerich, Kaifeng Yang, 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

Evolution Strategies for Laser Pulse Compression

Thomas Bäck, Lars Willmes, Janne Savolainen, 2007, Artificial Evolution.

Towards robustness optimization of complex networks based on redundancy backup

Thomas Bäck, Jun Wu, Michael T. M. Emmerich, 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

How to Do Recombination in Evolution Strategies: An Empirical Study

Thomas Bäck, Juan Chen, Michael T. M. Emmerich, 2009, IWINAC.

Cooling Strategies for the Moment-Generating Function in Bayesian Global Optimization

Hao Wang, Thomas Bäck, Michael T. M. Emmerich, 2018, 2018 IEEE Congress on Evolutionary Computation (CEC).

An evolutionary heuristic for the maximum independent set problem

Thomas Bäck, Sami Khuri, Thomas Bäck, 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

Introduction to the Special Issue: Self-Adaptation

Thomas Bäck, 2001 .

Routing optimization in corporate networks by evolutionary algorithms

Thomas Bäck, Claus Hillermeier, Jörg Ziegenhirt, 2003 .

Ant Colony Algorithms for the Dynamic Vehicle Routing Problem with Time Windows

Thomas Bäck, Michael T. M. Emmerich, Joost N. Kok, 2013, IWINAC.

SACOBRA with Online Whitening for Solving Optimization Problems with High Conditioning pdf

Thomas Bäck, Wolfgang Konen, Samineh Bagheri, 2019, ArXiv.

Combining Aggregation with Pareto Optimization: A Case Study in Evolutionary Molecular Design

Thomas Bäck, Michael T. M. Emmerich, Andreas Bender, 2009, EMO.

Evolution Strategies for Mixed-Integer Optimization of Optical Multilayer Systems

Thomas Bäck, Martin Schütz, Thomas Bäck, 1995, Evolutionary Programming.

Taxonomy of Evolution Strategies

Thomas Bäck, Peter Krause, Christophe Foussette, 2013 .

Optimizing a Medical Image Analysis System Using Mixed-Integer Evolution Strategies

Thomas Bäck, Michael Emmerich, Rui Li, 2009 .

Niching Methods: Speciation Theory Applied for Multi-modal Function Optimization

Thomas Bäck, Ofer M. Shir, Thomas Bäck, 2009, Algorithmic Bioprocesses.

An Overview of Parameter Control Methods by Self-Adaption in Evolutionary Algorithms

Thomas Bäck, Thomas Bäck, 1998, Fundam. Informaticae.

An evolutionary approach to combinatorial optimization problems

Thomas Bäck, Sami Khuri, Jörg Heitkötter, 1994, CSC '94.

Evolution strategies: basic introduction

Thomas Bäck, 2008, GECCO '08.

First Results Solving Arbitrarily Structured Maximum Independent Set Problems Using Quantum Annealing

Thomas Bäck, Aske Plaat, Sheir Yarkoni, 2018, 2018 IEEE Congress on Evolutionary Computation (CEC).

Machine Learning for Predicting the Impact Point of a Low Speed Vehicle Crash

Thomas Bäck, Milan Koch, Thomas Bäck, 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

Metamodel-assisted mixed integer evolution strategies and their application to intravascular ultrasound image analysis

Thomas Bäck, Michael T. M. Emmerich, Johan H. C. Reiber, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Evolutionary Computation 2 : Advanced Algorithms and Operators

Zbigniew Michalewicz, Thomas Bäck, David B. Fogel, 2000 .

Fundamental Concepts of Evolutionary Computation

Zbigniew Michalewicz, Günter Rudolph, Kalyanmoy Deb, 1997 .

Evolutionary Computation as a Paradigm for DNA-Based Computing

Thomas Bäck, Grzegorz Rozenberg, Joost N. Kok, 2002 .

On the log-normal self-adaptation of the mutation rate in binary search spaces

Thomas Bäck, Rui Li, Jeroen Eggermont, 2011, GECCO '11.

Algorithms for Simulation-Based Optimization Problems

Thomas Bäck, 2018, ECMS.

Evaluating Multi-criteria Evolutionary Algorithms for Airfoil Optimisation

Thomas Bäck, Werner Haase, Boris Naujoks, 2002, PPSN.

On the scalability of evolution strategies in the optimization of dynamic molecular alignment

Ofer M. Shir, Thomas Bäck, Marc J. J. Vrakking, 2007, GECCO '07.

Using the uncertainty handling CMA-ES for finding robust optima

Thomas Bäck, Michael T. M. Emmerich, Edgar Reehuis, 2011, GECCO '11.

A Superior Evolutionary Algorithm for 3-SAT

Thomas Bäck, A. E. Eiben, Marco E. Vink, 1998, Evolutionary Programming.

Vehicle Fleet Maintenance Scheduling Optimization by Multi-objective Evolutionary Algorithms

Yali Wang, Markus Olhofer, Thomas Bäck, 2019, 2019 IEEE Congress on Evolutionary Computation (CEC).

Optimizing traffic light controllers with evolutionary algorithms

Thomas Bäck, Mike Preuss, A. E. Eiben, 1998 .

Power Distribution Network Reconfiguration by Evolutionary Integer Programming

Thomas Bäck, Ji Wang, Michael T. M. Emmerich, 2014, PPSN.

Niche Radius Adaptation with Asymmetric Sharing

Ofer M. Shir, Thomas Bäck, Vincent van der Goes, 2008, PPSN.

Modeling Urban Growth by Cellular Automata

Thomas Bäck, Ulrich Hammel, Pierre Frankhauser, 1996, PPSN.

Evolutionary Algorithms in the Optimization of Dynamic Molecular Alignment

Ofer M. Shir, Thomas Bäck, Marc J. J. Vrakking, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Multi Objective Airfoil Design Using Single Parent Populations

Thomas Bäck, Werner Haase, Boris Naujoks, 2002, GECCO.

Evolutionary strategies for identification and validation of material model parameters for forming simulations

Thomas Bäck, Ingo Heinle, Lutz Keßler, 2011, GECCO '11.

Multicriteria Inventory Routing by Cooperative Swarms and Evolutionary Algorithms

Thomas Bäck, Michael T. M. Emmerich, Joost N. Kok, 2015, IWINAC.

An Archive Maintenance Scheme for Finding Robust Solutions

Thomas Bäck, Michael T. M. Emmerich, Johannes W. Kruisselbrink, 2010, PPSN.

Evolutionary algorithms in theorie and practice

Thomas Bäck, 1994 .

Learning Fluid Flows

Markus Olhofer, Thomas Bäck, Yu Liu, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Evolutionary Algorithms for Real World Applications

Thomas Bäck, Michael Emmerich, Thomas Bäck, 2008 .

Effects of Tax and Evolution in an Artificial Society

Thomas Bäck, A. E. Eiben, Daniel Vermeulen, 2002, JCIS.

Extended Selection Mechanisms in Genetic Algorithms

Thomas Bäck, Frank Hoffmeister, Thomas Bäck, 1991, ICGA.

A new acquisition function for Bayesian optimization based on the moment-generating function

Hao Wang, Thomas Bäck, Michael T. M. Emmerich, 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Multi-objective inventory routing with uncertain demand using population-based metaheuristics

Thomas Bäck, Michael T. M. Emmerich, Joost N. Kok, 2016, Integr. Comput. Aided Eng..

Boosting Quantum Annealing Performance Using Evolution Strategies for Annealing Offsets Tuning

Thomas Bäck, Hao Wang, Aske Plaat, 2019, QTOP@NetSys.

Multi-fidelity surrogate model approach to optimization

Markus Olhofer, Thomas Bäck, Matthijs van Leeuwen, 2018, GECCO.

Classification of Cell Fates with Support Vector Machine Learning

Ofer M. Shir, Thomas Bäck, Vered Raz, 2007, EvoBIO.

Configuring advanced evolutionary algorithms for multicriteria building spatial design optimisation

Thomas Bäck, Michael T. M. Emmerich, Koen van der Blom, 2017, 2017 IEEE Congress on Evolutionary Computation (CEC).

A New Repair Method For Constrained Optimization

Thomas Bäck, Peter Krause, Wolfgang Konen, 2015, GECCO.

The Interaction of Mutation Rate, Selection, and Self-Adaptation Within a Genetic Algorithm

Thomas Bäck, Thomas Bäck, 1992, PPSN.

Learning the Complete-Basis-Functions Parameterization for the Optimization of Dynamic Molecular Alignment by ES

Ofer M. Shir, Thomas Bäck, Joost N. Kok, 2006, IDEAL.

A multi-point mechanism of expected hypervolume improvement for parallel multi-objective bayesian global optimization

Thomas Bäck, Michael T. M. Emmerich, Pramudita Satria Palar, 2019, GECCO.

Towards Dynamic Fitness Based Partitioning for IntraVascular UltraSound Image Analysis

Thomas Bäck, Michael T. M. Emmerich, Johan H. C. Reiber, 2009, EvoWorkshops.

Introduction to evolution strategies

Thomas Bäck, 2014, GECCO.

On the evolution of laser pulses under a dynamic Quantum Control environment

Ofer M. Shir, Thomas Bäck, Herschel Rabitz, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Predict or screen your expensive assay: DoE vs. surrogates in experimental combinatorial optimization

Ofer M. Shir, Thomas Bäck, Naama Horesh, 2019, GECCO.

DNA computing of solutions to knapsack problems

Thomas Bäck, Grzegorz Rozenberg, Joost N. Kok, 2007, Biosyst..

Improved Evolutionary Algorithms for Scheduling Problems

Thomas Bäck, Guillermo Leguizamón, Raúl Héctor Gallard, 1999, German-Argentinian Workshop on Information Technology.

Convex Hull-Based Multi-objective Genetic Programming for Maximizing ROC Performance pdf

Xin Yao, Thomas Bäck, Michael T. M. Emmerich, 2013, ArXiv.

Gaining Insights into Laser Pulse Shaping by Evolution Strategies

Ofer M. Shir, Thomas Bäck, Joost N. Kok, 2007, IWINAC.

A Novel Uncertainty Quantification Method for Efficient Global Optimization

Hao Wang, Thomas Bäck, Wojtek Kowalczyk, 2018, IPMU.

Derivative-Free Chemical Process Synthesis by Memetic Algorithms Coupled to Aspen Plus Process Models

Thomas Bäck, Sebastian Engell, Maren Urselmann, 2016 .

Enhancing search space diversity in multi-objective evolutionary drug molecule design using niching

Thomas Bäck, Michael T. M. Emmerich, Andreas Bender, 2009, GECCO.

Evolution strategies for engineering design optimisation

Thomas Bäck, Lars Willmes, 2003 .

Towards multi-objective mixed integer evolution strategies

Thomas Bäck, Kaifeng Yang, Koen van der Blom, 2019 .

An Empirical Study on GAs "Without Parameters"

Thomas Bäck, A. E. Eiben, Nikolai A. L. van der Vaart, 2000, PPSN.

Novelty and interestingness measures for design-space exploration

Bernhard Sendhoff, Markus Olhofer, Thomas Bäck, 2013, GECCO '13.

Towards self-adaptive efficient global optimization

Hao Wang, Thomas Bäck, Michael Emmerich, 2019 .

Evolution strategies: basic introduction

Thomas Bäck, 2011, GECCO.

Mixed-integer evolution strategy using multiobjective selection applied to warehouse design optimization

Thomas Bäck, Edgar Reehuis, Thomas Bäck, 2010, GECCO '10.

Ant based solver for dynamic vehicle routing problem with time windows and multiple priorities

Thomas Bäck, Michael T. M. Emmerich, Zhiwei Yang, 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

Contemporary Evolution Strategies

Thomas Bäck, Peter Krause, Christophe Foussette, 2013, Natural Computing Series.

The Molecule Evoluator. An Interactive Evolutionary Algorithm for the Design of Drug-Like Molecules

Thomas Bäck, Joost N. Kok, Adriaan P. IJzerman, 2006, J. Chem. Inf. Model..

Book Review: Proceedings of the Fifth International Conference on Genetic Algorithms

Thomas Bäck, Thomas Bäck, 1994, Evolutionary Computation.

Comparing a Weiszfeld's-Based Procedure and (1+1)-es for Solving the Planar Single-Facility Location-Routing Problem

Thomas Bäck, Edgar Reehuis, Pepijn Van Heiningen, 2015, 2015 IEEE Symposium Series on Computational Intelligence.

Evolutionary computation: Toward a new philosophy of machine intelligence

Thomas Bäck, Thomas Bäck, 1997, Complex..

Hypervolume Indicator Gradient Ascent Multi-objective Optimization

Hao Wang, Thomas Bäck, Michael T. M. Emmerich, 2017, EMO.

Evolution strategies: basic introduction

Thomas Bäck, 2010, GECCO.

Mixed-Integer NK Landscapes

Thomas Bäck, Michael T. M. Emmerich, Johan H. C. Reiber, 2006, PPSN.

The complete-basis-functions parameterization in ES and its application to laser pulse shaping

Ofer M. Shir, Thomas Bäck, Marc J. J. Vrakking, 2006, GECCO.

Evolutionary algorithms for automated drug design towards target molecule properties

Thomas Bäck, Adriaan P. IJzerman, Eelke van der Horst, 2008, GECCO '08.

Self-Adaptive Niching CMA-ES with Mahalanobis Metric

Ofer M. Shir, Thomas Bäck, Michael T. M. Emmerich, 2007, 2007 IEEE Congress on Evolutionary Computation.

Semantische benadering van component-gebaseerde software

Thomas Bäck, A. E. Eiben, Walter A. Kosters, 2001 .

An Overview of Evolutionary Computation

Thomas Bäck, David B. Fogel, Hugo de Garis, 1993, ECML.

Identifying flight delay patterns using diverse subgroup discovery

Thomas Bäck, Matthijs van Leeuwen, Hugo Manuel Proença, 2018, 2018 IEEE Symposium Series on Computational Intelligence (SSCI).

Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms

Thomas Bäck, Thomas Bäck, 1996 .

Evolution Strategies: An Alternative Evolutionary Algorithm

Thomas Bäck, Thomas Bäck, 1995, Artificial Evolution.

Niche Radius Adaptation in the CMA-ES Niching Algorithm

Ofer M. Shir, Thomas Bäck, Thomas Bäck, 2006, PPSN.

SMS-EMOA with multiple dynamic reference points

Hao Wang, Thomas Bäck, Michael T. M. Emmerich, 2016, 2016 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD).

Evolutionary Computation Implementations

Günter Rudolph, Thomas Bäck, John J. Grefenstette, 1997 .

Bayesian performance analysis for black-box optimization benchmarking

Ofer M. Shir, Thomas Bäck, Borja Calvo, 2019, GECCO.

Online Adaptable Time Series Anomaly Detection with Discrete Wavelet Transforms and Multivariate Gaussian Distributions

Thomas Bäck, Wolfgang Konen, Markus Thill, 2018 .

Solving the G-problems in less than 500 iterations: Improved efficient constrained optimization by surrogate modeling and adaptive parameter control pdf

Thomas Bäck, Michael T. M. Emmerich, Wolfgang Konen, 2015, ArXiv.

Multi-objective genetic algorithms for reducing mark read-out effort in lithographic tests

Thomas Bäck, Pierluigi Frisco, Timo Bootsma, 2019, GECCO.

Metamodel-Assisted Evolution Strategies

Thomas Bäck, Michael T. M. Emmerich, Kyriakos C. Giannakoglou, 2002, PPSN.

Mixed-Integer Evolution Strategies with Dynamic Niching

Ofer M. Shir, Thomas Bäck, Michael T. M. Emmerich, 2008, PPSN.

Cluster-based Kriging approximation algorithms for complexity reduction

Hao Wang, Thomas Bäck, Michael T. M. Emmerich, 2017, Applied Intelligence.

Theory of Genetic Algorithms

Thomas Bäck, Walter A. Kosters, Joost N. Kok, 2001, Current Trends in Theoretical Computer Science.

Multi-objective aerodynamic design with user preference using truncated expected hypervolume improvement

Thomas Bäck, Michael T. M. Emmerich, Pramudita Satria Palar, 2018, GECCO.

Industrial Optimization by Evolution Strategies: A Bioinspired Optimization Algorithm

Thomas Bäck, Peter Krause, Lars Willmes, 2004, Informatica.

Performance analysis of derandomized evolution strategies in quantum control experiments

Ofer M. Shir, Thomas Bäck, Herschel Rabitz, 2008, GECCO '08.

Selection of a DFO Method for the Efficient Solution of Continuous Constrained Sub-Problems within a Memetic Algorithm for Chemical Process Synthesis

Thomas Bäck, Michael T. M. Emmerich, Sebastian Engell, 2016, GECCO.

Convex Hull-Based Multiobjective Genetic Programming for Maximizing Receiver Operating Characteristic Performance

Xin Yao, Thomas Bäck, Michael T. M. Emmerich, 2015, IEEE Transactions on Evolutionary Computation.

A semantic approach to component-based software

Thomas Bäck, A. E. Eiben, Walter A. Kosters, 2001 .

Evolutionäres Suchkonzept zum Aufstellen signifikanter Fuzzy-Regeln

Thomas Bäck, Angelika Krone, Peter Teuber, 1996 .

Multi-Objective Bayesian Global Optimization using expected hypervolume improvement gradient

Thomas Bäck, Michael T. M. Emmerich, Kaifeng Yang, 2019, Swarm Evol. Comput..

A Survey of Evolution Strategies

Thomas Bäck, Hans-Paul Schwefel, Frank Hoffmeister, 1991, ICGA.

Reconstructing fixed time traffic light cycles by camera data analytics

Thomas Bäck, Valentin Protschky, Marco Schönfelder, 2017, 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC).

Order Statistics for Convergence Velocity Analysis of Simplified Evolutionary Algorithms

Thomas Bäck, Thomas Bäck, 1994, FOGA.

Prototype Discovery using Quality-Diversity pdf

Thomas Bäck, Alexander Asteroth, Alexander Hagg, 2018, PPSN.

Handbook of Evolutionary Computation

Zbigniew Michalewicz, Thomas Bäck, David B. Fogel, 1997 .

Niching in Evolution Strategies and Its Application to Laser Pulse Shaping

Ofer M. Shir, Thomas Bäck, Marc J. J. Vrakking, 2005, Artificial Evolution.

Truncated expected hypervolume improvement: Exact computation and application

Thomas Bäck, Michael T. M. Emmerich, Kaifeng Yang, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Adaptive business intelligence based on evolution strategies: some application examples of self-adaptive software

Thomas Bäck, Thomas Bäck, 2002, Inf. Sci..

Automatic Configuration of Deep Neural Networks with EGO pdf

Hao Wang, Thomas Bäck, Bas van Stein, 2018, ArXiv.

Parallel Optimization of Evolutionary Algorithms

Thomas Bäck, Thomas Bäck, 1994, PPSN.

Evolutionary computation: comments on the history and current state

Thomas Bäck, Ulrich Hammel, Hans-Paul Schwefel, 1997, IEEE Trans. Evol. Comput..

Sequential experimentation by evolutionary algorithms

Ofer M. Shir, Thomas Bäck, Thomas Bäck, 2020, GECCO Companion.

Reducing complexity in many objective optimization using community detection

Thomas Bäck, Jing Liu, Zhongzhou Jiang, 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

Comparing neural networks and Kriging for fitness approximation in evolutionary optimization

Bernhard Sendhoff, Thomas Bäck, Yaochu Jin, 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

Self-adaptive mutation rates in genetic algorithm for inverse design of cellular automata

Thomas Bäck, Ron Breukelaar, Thomas Bäck, 2008, GECCO '08.

Solving optimization problems with high conditioning by means of online whitening

Thomas Bäck, Wolfgang Konen, Samineh Bagheri, 2019, GECCO.

Robust design of multilayer optical coatings by means of evolutionary algorithms

Thomas Bäck, Ulrich Hammel, Dirk Wiesmann, 1998, IEEE Trans. Evol. Comput..

Time complexity reduction in efficient global optimization using cluster kriging

Hao Wang, Thomas Bäck, Michael T. M. Emmerich, 2017, GECCO.

Optimizing Computed Tomographic Angiography Image Segmentation Using Fitness Based Partitioning

Thomas Bäck, Michael T. M. Emmerich, Johan H. C. Reiber, 2008, EvoWorkshops.

Evolving Transition Rules for Multi Dimensional Cellular Automata

Thomas Bäck, Ron Breukelaar, Thomas Bäck, 2004, ACRI.

SAMO-COBRA: A Fast Surrogate Assisted Constrained Multi-objective Optimization Algorithm

Thomas Bäck, Roy de Winter, Bas van Stein, 2021, EMO.

Addressing the multiplicity of solutions in optical lens design as a niching evolutionary algorithms computational challenge

Ofer M. Shir, Thomas Bäck, Pierluigi Frisco, 2021, GECCO Companion.

Explorative data analysis of time series based algorithm features of CMA-ES variants

Thomas Bäck, Hao Wang, Jacob de Nobel, 2021, GECCO.

Comparison of deep learning and hand crafted features for mining simulation data

Thomas Bäck, Michael S. Lew, Wei Chen, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Leveraging benchmarking data for informed one-shot dynamic algorithm selection

Thomas Bäck, Carola Doerr, Furong Ye, 2021, GECCO Companion.

Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules

Thomas Bäck, Carola Doerr, Diederick Vermetten, 2021, GECCO Companion.

Locating the local minima in lens design with machine learning

Ofer M. Shir, Thomas Bäck, Pierluigi Frisco, 2021, Optical Engineering + Applications.

Multiagent Deep Reinforcement Learning: Challenges and Directions Towards Human-Like Approaches pdf

Thomas Bäck, Aske Plaat, Anna V. Kononova, 2021, ArXiv.

IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics pdf

Thomas Bäck, Carola Doerr, Furong Ye, 2021, ArXiv.

Automated Configuration of Genetic Algorithms by Tuning for Anytime Performance pdf

Thomas Bäck, Carola Doerr, Furong Ye, 2021, ArXiv.

Quantum-Assisted Feature Selection for Vehicle Price Prediction Modeling pdf

Thomas Bäck, David Von Dollen, Florian Neukart, 2021, ArXiv.

Point2FFD: Learning Shape Representations of Simulation-Ready 3D Models for Engineering Design Optimization

Bernhard Sendhoff, Thomas Bäck, Stefan Menzel, 2021, 2021 International Conference on 3D Vision (3DV).

Temporal convolutional autoencoder for unsupervised anomaly detection in time series

Thomas Bäck, Wolfgang Konen, Markus Thill, 2021, Appl. Soft Comput..

Lifelong Computing pdf

Danny Weyns, Thomas Bäck, René Vidal, 2021, ArXiv.

Robust subgroup discovery pdf

Thomas Bäck, Matthijs van Leeuwen, Hugo Manuel Proença, 2021, ArXiv.

Improved Automated CASH Optimization with Tree Parzen Estimators for Class Imbalance Problems

Bernhard Sendhoff, Thomas Bäck, Stefan Menzel, 2021, 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA).

Expressivity of parameterized and data-driven representations in quality diversity search

Thomas Bäck, Simon Colton, Alexander Asteroth, 2021, GECCO.

Exploiting Local Geometric Features in Vehicle Design Optimization with 3D Point Cloud Autoencoders

Bernhard Sendhoff, Thomas Bäck, Stefan Menzel, 2021, 2021 IEEE Congress on Evolutionary Computation (CEC).

A Classification-based Solution For Recommending Process Parameters of Production Processes Without Quality Measures

Thomas Bäck, Ingo Heinle, Hao Wang, 2021 .

Solving the Shipment Rerouting Problem with Quantum Optimization Techniques

Hanno Schülldorf, Thomas Bäck, Benjamin Speitkamp, 2021, ICCL.

Preprint: Norm Loss: An efficient yet effective regularization method for deep neural networks pdf

Thomas Bäck, Michael S. Lew, Wei Chen, 2021, ArXiv.

Requirements towards optimizing analytics in industrial processes

Thomas Bäck, Bas van Stein, Alexander Zeiser, 2021, ANT/EDI40.

Sequential experimentation by evolutionary algorithms

Ofer M. Shir, Thomas Bäck, Thomas Bäck, 2021, GECCO Companion.

Norm Loss: An efficient yet effective regularization method for deep neural networks

Thomas Bäck, Michael S. Lew, Sebastian Schmitt, 2021, 2020 25th International Conference on Pattern Recognition (ICPR).

Multi-car paint shop optimization with quantum annealing

Thomas Bäck, David Von Dollen, Florian Neukart, 2021, 2021 IEEE International Conference on Quantum Computing and Engineering (QCE).

A new acquisition function for robust Bayesian optimization of unconstrained problems

Bernhard Sendhoff, Thomas Bäck, Stefan Menzel, 2021, GECCO Companion.

Optimizing the maintenance schedule for a vehicle fleet: a simulation-based case study

Markus Olhofer, Thomas Bäck, Michael Emmerich, 2021 .

Accelerated optimization and automated discovery with covariance matrix adaptation for experimental quantum control

Ofer M. Shir, Thomas Bäck, Herschel Rabitz, 2009 .

GPCR NaVa database: natural variants in human G protein‐coupled receptors

Thomas Bäck, Joost Kok, Jeroen Kazius, 2008, Human mutation.

Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms

Thomas Bäck, Thomas Bäck, Peter Krause, 2019, ICDM.

Model-guided Evolution Strategies for Dynamically Balancing Exploration and Exploitation

Bernhard Sendhoff, Markus Olhofer, Thomas Bäck, 2011 .

Optimal Control of Biogas Plants Using Nonlinear MPC

Thomas Bäck, Seán McLoone, Daniel Gaida, 2011 .

Characteristic amino acid combinations in olfactory G protein‐coupled receptors

Thomas Bäck, Peter Krause, Thomas Bäck, 2007, Proteins.