A Topology Exploiting Genetic Algorithm to Control Dynamic Systems. - Dirk Thierens; Leo Vercauteren (PPSN, 1990)

Mixing in Genetic Algorithms. - Dirk Thierens; David E. Goldberg (ICGA, 1993)

Elitist Recombination: An Integrated Selection Recombination GA. - Dirk Thierens; David E. Goldberg (International Conference on Evolutionary Computation, 1994)

Convergence Models of Genetic Algorithm Selection Schemes. - Dirk Thierens; David E. Goldberg (PPSN, 1994)

Non-Redundant Genetic Coding of Neural Networks. - Dirk Thierens (International Conference on Evolutionary Computation, 1996)

Dimensional Analysis of Allele-Wise Mixing Revisited. - Dirk Thierens (PPSN, 1996)

Selection Schemes, Elitist Recombination, and Selection Intensity. - Dirk Thierens (ICGA, 1997)

A case study of a multiobjective recombinative genetic algorithm with coevolutionary sharing. - Martijn Neef; Dirk Thierens; Henryk F. R. Arciszewski (CEC, 1999)

Linkage Information Processing In Distribution Estimation Algorithms. - Peter A. N. Bosman; Dirk Thierens (GECCO, 1999)

On The Design of Genetic Algorithms for Geographical Applications. - Steven van Dijk; Dirk Thierens; Mark de Berg (GECCO, 1999)

Scalability Problems of Simple Genetic Algorithms. - Dirk Thierens (Evol. Comput., 1999)

Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA. - Peter A. N. Bosman; Dirk Thierens (PPSN, 2000)

Scalability and Efficiency of Genetic Algorithms for Geometrical Applications. - Steven van Dijk; Dirk Thierens; Mark de Berg (PPSN, 2000)

Computation in Gene Expression. - Hillol Kargupta; Dirk Thierens (Complex Syst., 2001)

Adaptive mutation rate control schemes in genetic algorithms. - Dirk Thierens (IEEE Congress on Evolutionary Computation, 2002)

Permutation Optimization by Iterated Estimation of Random Keys Marginal Product Factorizations. - Peter A. N. Bosman; Dirk Thierens (PPSN, 2002)

Using Genetic Algorithms for Solving Hard Problems in GIS. - Steven van Dijk; Dirk Thierens; Mark de Berg (GeoInformatica, 2002)

Multi-objective optimization with diversity preserving mixture-based iterated density estimation evolutionary algorithms. - Peter A. N. Bosman; Dirk Thierens (Int. J. Approx. Reason., 2002)

Evolutionary Markov Chain Monte Carlo. - Madalina M. Drugan; Dirk Thierens (Artificial Evolution, 2003)

Convergence Time Analysis for the Multi-objective Counting Ones Problem. - Dirk Thierens (EMO, 2003)

Building a GA from Design Principles for Learning Bayesian Networks. - Steven van Dijk; Dirk Thierens; Linda C. van der Gaag (GECCO, 2003)

A Skeleton-Based Approach to Learning Bayesian Networks from Data. - Steven van Dijk; Linda C. van der Gaag; Dirk Thierens (PKDD, 2003)

The balance between proximity and diversity in multiobjective evolutionary algorithms. - Peter A. N. Bosman; Dirk Thierens (IEEE Trans. Evol. Comput., 2003)

Exploiting Modularity, Hierarchy, and Repetition in Variable-Length Problems. - Edwin D. de Jong; Dirk Thierens (GECCO (1), 2004)

Population-Based Iterated Local Search: Restricting Neighborhood Search by Crossover. - Dirk Thierens (GECCO (2), 2004)

On the Use of a Non-redundant Encoding for Learning Bayesian Networks from Data with a GA. - Steven van Dijk; Dirk Thierens (PPSN, 2004)

Hierarchical Genetic Algorithms. - Edwin D. de Jong; Dirk Thierens; Richard A. Watson (PPSN, 2004)

On the Design and Analysis of Competent Selecto-recombinative GAs. - Steven van Dijk; Dirk Thierens; Mark de Berg (Evol. Comput., 2004)

Recombinative EMCMC algorithms. - Madalina M. Drugan; Dirk Thierens (Congress on Evolutionary Computation, 2005)

The Naive MIDEA: A Baseline Multi-objective EA. - Peter A. N. Bosman; Dirk Thierens (EMO, 2005)

On the complexity of hierarchical problem solving. - Edwin D. de Jong; Richard A. Watson; Dirk Thierens (GECCO, 2005)

A generator for hierarchical problems. - Edwin D. de Jong; Richard A. Watson; Dirk Thierens (GECCO Workshops, 2005)

An adaptive pursuit strategy for allocating operator probabilities. - Dirk Thierens (GECCO, 2005)

Multi-objective Optimization with the Naive 𝕄 ID 𝔼 A. - Peter A. N. Bosman; Dirk Thierens (Towards a New Evolutionary Computation, 2006)

Exploration and Exploitation Bias of Crossover and Path Relinking for Permutation Problems. - Dirk Thierens (PPSN, 2006)

Numerical Optimization with Real-Valued Estimation-of-Distribution Algorithms. - Peter A. N. Bosman; Dirk Thierens (Scalable Optimization via Probabilistic Modeling, 2006)

Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms. - Peter A. N. Bosman; Dirk Thierens (GECCO, 2007)

Adaptive Strategies for Operator Allocation. - Dirk Thierens (Parameter Setting in Evolutionary Algorithms, 2007)

A bivariate probabilistic model-building genetic algorithm for graph bipartitioning. - Dirk Thierens (GECCO (Companion), 2008)

Enhancing the Performance of Maximum-Likelihood Gaussian EDAs Using Anticipated Mean Shift. - Peter A. N. Bosman; Jörn Grahl; Dirk Thierens (PPSN, 2008)

AMaLGaM IDEAs in noiseless black-box optimization benchmarking. - Peter A. N. Bosman; Jörn Grahl; Dirk Thierens (GECCO (Companion), 2009)

AMaLGaM IDEAs in noisy black-box optimization benchmarking. - Peter A. N. Bosman; Jörn Grahl; Dirk Thierens (GECCO (Companion), 2009)

On benchmark properties for adaptive operator selection. - Dirk Thierens (GECCO (Companion), 2009)

Adaptive Operator Selection for Iterated Local Search. - Dirk Thierens (SLS, 2009)

Linkage tree genetic algorithm: first results. - Dirk Thierens (GECCO (Companion), 2010)

Path-Guided Mutation for Stochastic Pareto Local Search Algorithms. - Madalina M. Drugan; Dirk Thierens (PPSN (1), 2010)

The Linkage Tree Genetic Algorithm. - Dirk Thierens (PPSN (1), 2010)

Geometrical Recombination Operators for Real-Coded Evolutionary MCMCs. - Madalina M. Drugan; Dirk Thierens (Evol. Comput., 2010)

Recombination operators and selection strategies for evolutionary Markov Chain Monte Carlo algorithms. - Madalina M. Drugan; Dirk Thierens (Evol. Intell., 2010)

The roles of local search, model building and optimal mixing in evolutionary algorithms from a bbo perspective. - Peter A. N. Bosman; Dirk Thierens (GECCO (Companion), 2011)

Generalized adaptive pursuit algorithm for genetic pareto local search algorithms. - Madalina M. Drugan; Dirk Thierens (GECCO, 2011)

Pairwise and problem-specific distance metrics in the linkage tree genetic algorithm. - Martin Pelikan; Mark Hauschild; Dirk Thierens (GECCO, 2011)

Optimal mixing evolutionary algorithms. - Dirk Thierens; Peter A. N. Bosman (GECCO, 2011)

Linkage neighbors, optimal mixing and forced improvements in genetic algorithms. - Peter A. N. Bosman; Dirk Thierens (GECCO, 2012)

Predetermined versus learned linkage models. - Dirk Thierens; Peter A. N. Bosman (GECCO, 2012)

Learning the Neighborhood with the Linkage Tree Genetic Algorithm. - Dirk Thierens; Peter A. N. Bosman (LION, 2012)

On Measures to Build Linkage Trees in LTGA. - Peter A. N. Bosman; Dirk Thierens (PPSN (1), 2012)

Evolvability Analysis of the Linkage Tree Genetic Algorithm. - Dirk Thierens; Peter A. N. Bosman (PPSN (1), 2012)

Stochastic Pareto local search: Pareto neighbourhood exploration and perturbation strategies. - Madalina M. Drugan; Dirk Thierens (J. Heuristics, 2012)

More concise and robust linkage learning by filtering and combining linkage hierarchies. - Peter A. N. Bosman; Dirk Thierens (GECCO, 2013)

On the usefulness of linkage processing for solving MAX-SAT. - Krzysztof L. Sadowski; Peter A. N. Bosman; Dirk Thierens (GECCO, 2013)

Hierarchical problem solving with the linkage tree genetic algorithm. - Dirk Thierens; Peter A. N. Bosman (GECCO, 2013)

Benchmarking Parameter-Free AMaLGaM on Functions With and Without Noise. - Peter A. N. Bosman; Jörn Grahl; Dirk Thierens (Evol. Comput., 2013)

Model-based evolutionary algorithms. - Dirk Thierens; Peter A. N. Bosman (GECCO (Companion), 2014)

Combining Model-Based EAs for Mixed-Integer Problems. - Krzysztof L. Sadowski; Dirk Thierens; Peter A. N. Bosman (PPSN, 2014)

In Search of Optimal Linkage Trees. - Roy de Bokx; Dirk Thierens; Peter A. N. Bosman (GECCO (Companion), 2015)

A Clustering-Based Model-Building EA for Optimization Problems with Binary and Real-Valued Variables. - Krzysztof L. Sadowski; Peter A. N. Bosman; Dirk Thierens (GECCO, 2015)

Learning and exploiting mixed variable dependencies with a model-based EA. - Krzysztof L. Sadowski; Peter A. N. Bosman; Dirk Thierens (CEC, 2016)

Expanding from Discrete Cartesian to Permutation Gene-pool Optimal Mixing Evolutionary Algorithms. - Peter A. N. Bosman; Ngoc Hoang Luong; Dirk Thierens (GECCO, 2016)

The Multiple Insertion Pyramid: A Fast Parameter-Less Population Scheme. - Willem den Besten; Dirk Thierens; Peter A. N. Bosman (PPSN, 2016)

Niching an estimation-of-distribution algorithm by hierarchical Gaussian mixture learning. - S. C. Maree; Tanja Alderliesten; Dirk Thierens; Peter A. N. Bosman (GECCO, 2017)

Exploring trade-offs between target coverage, healthy tissue sparing, and the placement of catheters in HDR brachytherapy for prostate cancer using a novel multi-objective model-based mixed-integer evolutionary algorithm. - Krzysztof L. Sadowski; Marjolein C. van der Meer; Ngoc Hoang Luong; Tanja Alderliesten; Dirk Thierens; Rob van der Laarse; Yury Niatsetski; Arjan Bel; Peter A. N. Bosman (GECCO, 2017)

Model-based evolutionary algorithms: GECCO 2017 tutorial. - Dirk Thierens; Peter A. N. Bosman (GECCO (Companion), 2017)

Real-valued evolutionary multi-modal optimization driven by hill-valley clustering. - S. C. Maree; Tanja Alderliesten; Dirk Thierens; Peter A. N. Bosman (GECCO, 2018)

Learning bayesian network structures with GOMEA. - Kalia Orphanou; Dirk Thierens; Peter A. N. Bosman (GECCO, 2018)

Model-based evolutionary algorithms: GECCO 2018 tutorial. - Dirk Thierens; Peter A. N. Bosman (GECCO (Companion), 2018)

Heuristics in Permutation GOMEA for Solving the Permutation Flowshop Scheduling Problem. - G. H. Aalvanger; Ngoc Hoang Luong; Peter A. N. Bosman; Dirk Thierens (PPSN (1), 2018)

Benchmarking the Hill-Valley Evolutionary Algorithm for the GECCO 2018 Competition on Niching Methods Multimodal Optimization. - S. C. Maree; Tanja Alderliesten; Dirk Thierens; Peter A. N. Bosman (CoRR, 2018)

GAMBIT: A Parameterless Model-Based Evolutionary Algorithm for Mixed-Integer Problems. - Krzysztof L. Sadowski; Dirk Thierens; Peter A. N. Bosman (Evol. Comput., 2018)

Investigation of the traveling thief problem. - Rogier Hans Wuijts; Dirk Thierens (GECCO, 2019)

Model-based evolutionary algorithms: GECCO 2020 tutorial. - Dirk Thierens; Peter A. N. Bosman (GECCO Companion, 2020)

Benchmark generator for TD Mk landscapes. - Tobias van Driessel; Dirk Thierens (GECCO Companion, 2021)

Hybrid linkage learning for permutation optimization with Gene-pool optimal mixing evolutionary algorithms. - Michal Witold Przewozniczek; Marcin M. Komarnicki; Peter A. N. Bosman; Dirk Thierens; Bartosz Frej; Ngoc Hoang Luong (GECCO Companion, 2021)

Optimization of multi-objective mixed-integer problems with a model-based evolutionary algorithm in a black-box setting. - Krzysztof L. Sadowski; Dirk Thierens; Peter A. N. Bosman (GECCO Companion, 2021)

A benchmark generator of tree decomposition Mk landscapes. - Dirk Thierens; Tobias van Driessel (GECCO Companion, 2021)

A reliable ensemble based approach to semi-supervised learning. - Sjoerd de Vries; Dirk Thierens (Knowl. Based Syst., 2021)

Two-Phase Real-Valued Multimodal Optimization with the Hill-Valley Evolutionary Algorithm. - Stefanus C. Maree; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (Metaheuristics for Finding Multiple Solutions, 2021)

Solving multi-structured problems by introducing linkage kernels into GOMEA. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2022)

Model-based evolutionary algorithms: GECCO 2022 tutorial. - Dirk Thierens; Peter A. N. Bosman (GECCO Companion, 2022)

A semi-supervised decision support system to facilitate antibiotic stewardship for urinary tract infections. - Sjoerd de Vries; Thijs ten Doesschate; Joan E. E. Totté; Judith W. Heutz; Yvette G. T. Loeffen; Jan Jelrik Oosterheert; Dirk Thierens; Edwin Boel (Comput. Biol. Medicine, 2022)

Solving multi-structured problems by introducing linkage kernels into GOMEA - Source Code. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (Zenodo, 2022)

The Impact of Asynchrony on Parallel Model-Based EAs. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (GECCO, 2023)

Generating the Ground Truth: Synthetic Data for Label Noise Research. - Sjoerd de Vries; Dirk Thierens (CoRR, 2023)

Impact of Asynchrony on MBEAs - Source Code. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (Zenodo, 2023)

Exploring the Search Space of Neural Network Combinations obtained with Efficient Model Stitching. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (GECCO Companion, 2024)

Stitching for Neuroevolution: Recombining Deep Neural Networks without Breaking Them. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (CoRR, 2024)

Learning with Confidence: Training Better Classifiers from Soft Labels. - Sjoerd de Vries; Dirk Thierens (CoRR, 2024)

Parameterless Gene-Pool Optimal Mixing Evolutionary Algorithms. - Arkadiy Dushatskiy; Marco Virgolin; Anton Bouter; Dirk Thierens; Peter A. N. Bosman (Evol. Comput., 2024)

Exploring the Search Space of Neural Network Combinations obtained with Efficient Model Stitching - Source Code. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (Zenodo, 2024)

Exploring the Search Space of Neural Network Combinations obtained with Efficient Model Stitching - Results Data. - Arthur Guijt; Dirk Thierens; Tanja Alderliesten; Peter A. N. Bosman (Zenodo, 2024)

The Pitfalls and Potentials of Adding Gene-invariance to Optimal Mixing. - Anton Bouter; Dirk Thierens; Peter A. N. Bosman (CoRR, 2025)