| 2026 | GECCO | Parallel Adaptive Multi-Objective Evolutionary Learning of Discretized Bayesian Network Classifiers for Clinical Data. | Damy M. F. Ha, Thalea Schlender, Yvette van der Linden, Peter A. N. Bosman, Tanja Alderliesten |
| 2026 | GECCO | Introns and Templates Matter: Rethinking Linkage in GP-GOMEA. | Johannes Koch, Tanja Alderliesten, Peter A. N. Bosman |
| 2026 | GECCO | Model-Based Evolutionary Algorithms. | Dirk Thierens, Peter A. N. Bosman |
| 2025 | FOGA | Conditional Direct Empirical Linkage Discovery for Solving Multi-Structured Problems. | Michal Witold Przewozniczek, Peter A. N. Bosman, Anton Bouter, Arthur Guijt, Marcin M. Komarnicki, Dirk Thierens |
| 2025 | GECCO | The Pitfalls and Potentials of Adding Gene-invariance to Optimal Mixing. | Anton Bouter, Dirk Thierens, Peter A. N. Bosman |
| 2025 | GECCO | A Better Multi-Objective GP-GOMEA - But do we Need it? | Joe Harrison, Tanja Alderliesten, Peter A. N. Bosman |
| 2025 | GECCO | A Step towards Interpretable Multimodal AI Models with MultiFIX. | Mafalda Malafaia, Thalea Schlender, Tanja Alderliesten, Peter A. N. Bosman |
| 2025 | GECCO | More Efficient Real-Valued Gray-Box Optimization through Incremental Distribution Estimation in RV-GOMEA. | Renzo J. Scholman, Tanja Alderliesten, Peter A. N. Bosman |
| 2025 | GECCO | Model-Based Evolutionary Algorithms. | Dirk Thierens, Peter A. N. Bosman |
| 2024 | GECCO | Fitness-based Linkage Learning and Maximum-Clique Conditional Linkage Modelling for Gray-box Optimization with RV-GOMEA. | Georgios Andreadis, Tanja Alderliesten, Peter A. N. Bosman |
| 2024 | GECCO | Exploring the Search Space of Neural Network Combinations obtained with Efficient Model Stitching. | Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman |
| 2024 | GECCO | Temporal True and Surrogate Fitness Landscape Analysis for Expensive Bi-Objective Optimisation. | Cedric J. Rodriguez, Sarah L. Thomson, Tanja Alderliesten, Peter A. N. Bosman |
| 2024 | GECCO | Improving the efficiency of GP-GOMEA for higher-arity operators. | Thalea Schlender, Mafalda Malafaia, Tanja Alderliesten, Peter A. N. Bosman |
| 2024 | GECCO | Function Class Learning with Genetic Programming: Towards Explainable Meta Learning for Tumor Growth Functionals. | Evi Sijben, Jeroen C. Jansen, Peter A. N. Bosman, Tanja Alderliesten |
| 2024 | GECCO | Model-Based Evolutionary Algorithms. | Dirk Thierens, Peter A. N. Bosman |
| 2024 | PPSN | Learning Discretized Bayesian Networks with GOMEA. | Damy M. F. Ha, Tanja Alderliesten, Peter A. N. Bosman |
| 2024 | PPSN | Simultaneous Model-Based Evolution of Constants and Expression Structure in GP-GOMEA for Symbolic Regression. | Johannes Koch, Tanja Alderliesten, Peter A. N. Bosman |
| 2024 | PPSN | Balancing Between Time Budgets and Costs in Surrogate-Assisted Evolutionary Algorithms. | Cedric J. Rodriguez, Peter A. N. Bosman, Tanja Alderliesten |
| 2023 | ECAI | Shrink-Perturb Improves Architecture Mixing During Population Based Training for Neural Architecture Search. | Alexander Chebykin, Arkadiy Dushatskiy, Tanja Alderliesten, Peter A. N. Bosman |
| 2023 | EMO | Multi-objective Learning Using HV Maximization. | Timo M. Deist, Monika Grewal, Frank J. W. M. Dankers, Tanja Alderliesten, Peter A. N. Bosman |
| 2023 | GECCO | MOREA: a GPU-accelerated Evolutionary Algorithm for Multi-Objective Deformable Registration of 3D Medical Images. | Georgios Andreadis, Peter A. N. Bosman, Tanja Alderliesten |
| 2023 | GECCO | A Joint Python/C++ Library for Efficient yet Accessible Black-Box and Gray-Box Optimization with GOMEA. | Anton Bouter, Peter A. N. Bosman |
| 2023 | GECCO | The Impact of Asynchrony on Parallel Model-Based EAs. | Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman |
| 2023 | GECCO | Mini-Batching, Gradient-Clipping, First- versus Second-Order: What Works in Gradient-Based Coefficient Optimisation for Symbolic Regression? | Joe Harrison, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman |
| 2023 | GECCO | Model-Based Evolutionary Algorithms. | Dirk Thierens, Peter A. N. Bosman |
| 2023 | ICML | Multi-Objective Population Based Training. | Arkadiy Dushatskiy, Alexander Chebykin, Tanja Alderliesten, Peter A. N. Bosman |
| 2022 | GECCO | GPU-accelerated parallel gene-pool optimal mixing in a gray-box optimization setting. | Anton Bouter, Peter A. N. Bosman |
| 2022 | GECCO | Evolutionary neural cascade search across supernetworks. | Alexander Chebykin, Tanja Alderliesten, Peter A. N. Bosman |
| 2022 | GECCO | Adaptive objective configuration in bi-objective evolutionary optimization for cervical cancer brachytherapy treatment planning. | Leah R. M. Dickhoff, Ellen M. Kerkhof, Heloisa H. Deuzeman, Carien L. Creutzberg, Tanja Alderliesten, Peter A. N. Bosman |
| 2022 | GECCO | Heed the noise in performance evaluations in neural architecture search. | Arkadiy Dushatskiy, Tanja Alderliesten, Peter A. N. Bosman |
| 2022 | GECCO | Solving multi-structured problems by introducing linkage kernels into GOMEA. | Arthur Guijt, Dirk Thierens, Tanja Alderliesten, Peter A. N. Bosman |
| 2022 | GECCO | Evolvability degeneration in multi-objective genetic programming for symbolic regression. | Dazhuang Liu, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman |
| 2022 | GECCO | Multi-modal multi-objective model-based genetic programming to find multiple diverse high-quality models. | E. M. C. Sijben, Tanja Alderliesten, Peter A. N. Bosman |
| 2022 | GECCO | Model-based evolutionary algorithms: GECCO 2022 tutorial. | Dirk Thierens, Peter A. N. Bosman |
| 2022 | GECCO | On genetic programming representations and fitness functions for interpretable dimensionality reduction. | Thomas Uriot, Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman |
| 2022 | GECCO | Coefficient mutation in the gene-pool optimal mixing evolutionary algorithm for symbolic regression. | Marco Virgolin, Peter A. N. Bosman |
| 2022 | PPSN | Hybridizing Hypervolume-Based Evolutionary Algorithms and Gradient Descent by Dynamic Resource Allocation. | Damy M. F. Ha, Timo M. Deist, Peter A. N. Bosman |
| 2022 | PPSN | Gene-pool Optimal Mixing in Cartesian Genetic Programming. | Joe Harrison, Tanja Alderliesten, Peter A. N. Bosman |
| 2022 | PPSN | Obtaining Smoothly Navigable Approximation Sets in Bi-objective Multi-modal Optimization. | Renzo J. Scholman, Anton Bouter, Leah R. M. Dickhoff, Tanja Alderliesten, Peter A. N. Bosman |
| 2021 | CEC | GPU-Accelerated Parallel Gene-pool Optimal Mixing Applied to Multi-Objective Deformable Image Registration. | Anton Bouter, Tanja Alderliesten, Peter A. N. Bosman |
| 2021 | EMO | Local Search is a Remarkably Strong Baseline for Neural Architecture Search. | Tom Den Ottelander, Arkadiy Dushatskiy, Marco Virgolin, Peter A. N. Bosman |
| 2021 | GECCO | A novel surrogate-assisted evolutionary algorithm applied to partition-based ensemble learning. | Arkadiy Dushatskiy, Tanja Alderliesten, Peter A. N. Bosman |
| 2021 | GECCO | 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 |
| 2021 | GECCO | 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 |
| 2021 | GECCO | Model-based evolutionary algorithms. | Dirk Thierens, Peter A. N. Bosman |
| 2020 | GECCO | Leveraging conditional linkage models in gray-box optimization with the real-valued gene-pool optimal mixing evolutionary algorithm. | Anton Bouter, Stefanus C. Maree, Tanja Alderliesten, Peter A. N. Bosman |
| 2020 | GECCO | Model-based evolutionary algorithms: GECCO 2020 tutorial. | Dirk Thierens, Peter A. N. Bosman |
| 2020 | PPSN | Multi-objective Optimization by Uncrowded Hypervolume Gradient Ascent. | Timo M. Deist, Stefanus C. Maree, Tanja Alderliesten, Peter A. N. Bosman |
| 2020 | PPSN | Ensuring Smoothly Navigable Approximation Sets by Bzier Curve Parameterizations in Evolutionary Bi-objective Optimization. | Stefanus C. Maree, Tanja Alderliesten, Peter A. N. Bosman |
| 2020 | PPSN | Robust Evolutionary Bi-objective Optimization for Prostate Cancer Treatment with High-Dose-Rate Brachytherapy. | Marjolein C. van der Meer, Arjan Bel, Yury Niatsetski, Tanja Alderliesten, Bradley R. Pieters, Peter A. N. Bosman |
| 2019 | GECCO | Convolutional neural network surrogate-assisted GOMEA. | Arkadiy Dushatskiy, Adrinne M. Mendrik, Tanja Alderliesten, Peter A. N. Bosman |
| 2019 | GECCO | Real-valued evolutionary multi-modal multi-objective optimization by hill-valley clustering. | S. C. Maree, Tanja Alderliesten, Peter A. N. Bosman |
| 2019 | GECCO | Toward self-learning model-based EAs. | Erik A. Meulman, Peter A. N. Bosman |
| 2019 | GECCO | Model-based evolutionary algorithms. | Dirk Thierens, Peter A. N. Bosman |
| 2019 | GECCO | Linear scaling with and within semantic backpropagation-based genetic programming for symbolic regression. | Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman |
| 2018 | GECCO | Large-scale parallelization of partial evaluations in evolutionary algorithms for real-world problems. | Anton Bouter, Tanja Alderliesten, Arjan Bel, Cees Witteveen, Peter A. N. Bosman |
| 2018 | GECCO | Improving the performance of MO-RV-GOMEA on problems with many objectives using tchebycheff scalarizations. | Ngoc Hoang Luong, Tanja Alderliesten, Peter A. N. Bosman |
| 2018 | GECCO | Real-valued evolutionary multi-modal optimization driven by hill-valley clustering. | S. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman |
| 2018 | GECCO | Better and faster catheter position optimization in HDR brachytherapy for prostate cancer using multi-objective real-valued GOMEA. | Marjolein C. van der Meer, Bradley R. Pieters, Yury Niatsetski, Tanja Alderliesten, Arjan Bel, Peter A. N. Bosman |
| 2018 | GECCO | Learning bayesian network structures with GOMEA. | Kalia Orphanou, Dirk Thierens, Peter A. N. Bosman |
| 2018 | GECCO | Model-based evolutionary algorithms: GECCO 2018 tutorial. | Dirk Thierens, Peter A. N. Bosman |
| 2018 | GECCO | Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors. | Marco Virgolin, Tanja Alderliesten, Arjan Bel, Cees Witteveen, Peter A. N. Bosman |
| 2018 | PPSN | Heuristics in Permutation GOMEA for Solving the Permutation Flowshop Scheduling Problem. | G. H. Aalvanger, Ngoc Hoang Luong, Peter A. N. Bosman, Dirk Thierens |
| 2017 | GECCO | Exploiting linkage information in real-valued optimization with the real-valued gene-pool optimal mixing evolutionary algorithm. | Anton Bouter, Tanja Alderliesten, Cees Witteveen, Peter A. N. Bosman |
| 2017 | GECCO | The multi-objective real-valued gene-pool optimal mixing evolutionary algorithm. | Anton Bouter, Ngoc Hoang Luong, Cees Witteveen, Tanja Alderliesten, Peter A. N. Bosman |
| 2017 | GECCO | Spatial redistribution of irregularly-spaced pareto fronts for more intuitive navigation and solution selection. | Anton Bouter, Kleopatra Pirpinia, Tanja Alderliesten, Peter A. N. Bosman |
| 2017 | GECCO | Efficient, effective, and insightful tackling of the high-dose-rate brachytherapy treatment planning problem for prostate cancer using evolutionary multi-objective optimization algorithms. | Ngoc Hoang Luong, Anton Bouter, Marjolein C. van der Meer, Yury Niatsetski, Cees Witteveen, Arjan Bel, Tanja Alderliesten, Peter A. N. Bosman |
| 2017 | GECCO | Niching an estimation-of-distribution algorithm by hierarchical Gaussian mixture learning. | S. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman |
| 2017 | GECCO | 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 |
| 2017 | GECCO | Model-based evolutionary algorithms: GECCO 2017 tutorial. | Dirk Thierens, Peter A. N. Bosman |
| 2017 | GECCO | Scalable genetic programming by gene-pool optimal mixing and input-space entropy-based building-block learning. | Marco Virgolin, Tanja Alderliesten, Cees Witteveen, Peter A. N. Bosman |
| 2016 | CEC | Learning and exploiting mixed variable dependencies with a model-based EA. | Krzysztof L. Sadowski, Peter A. N. Bosman, Dirk Thierens |
| 2016 | GECCO | Expanding from Discrete Cartesian to Permutation Gene-pool Optimal Mixing Evolutionary Algorithms. | Peter A. N. Bosman, Ngoc Hoang Luong, Dirk Thierens |
| 2016 | GECCO | GECCO'16 Model-Based Evolutionary Algorithms (MBEA) Workshop Chairs' Welcome. | Peter A. N. Bosman, John A. W. McCall |
| 2016 | GECCO | Model-Based Evolutionary Algorithms. | Dirk Thierens, Peter A. N. Bosman |
| 2016 | PPSN | The Multiple Insertion Pyramid: A Fast Parameter-Less Population Scheme. | Willem den Besten, Dirk Thierens, Peter A. N. Bosman |
| 2015 | GECCO | In Search of Optimal Linkage Trees. | Roy de Bokx, Dirk Thierens, Peter A. N. Bosman |
| 2015 | GECCO | Exploiting Linkage Information and Problem-Specific Knowledge in Evolutionary Distribution Network Expansion Planning. | Ngoc Hoang Luong, Han La Poutr, Peter A. N. Bosman |
| 2015 | GECCO | Diversifying Multi-Objective Gradient Techniques and their Role in Hybrid Multi-Objective Evolutionary Algorithms for Deformable Medical Image Registration. | Kleopatra Pirpinia, Tanja Alderliesten, Jan-Jakob Sonke, Marcel van Herk, Peter A. N. Bosman |
| 2015 | GECCO | A Clustering-Based Model-Building EA for Optimization Problems with Binary and Real-Valued Variables. | Krzysztof L. Sadowski, Peter A. N. Bosman, Dirk Thierens |
| 2015 | GECCO | Model-Based Evolutionary Algorithms. | Dirk Thierens, Peter A. N. Bosman |
| 2014 | GECCO | Efficiency enhancements for evolutionary capacity planning in distribution grids. | Ngoc Hoang Luong, Marinus O. W. Grond, Han La Poutr, Peter A. N. Bosman |
| 2014 | GECCO | Multi-objective gene-pool optimal mixing evolutionary algorithms. | Ngoc Hoang Luong, Han La Poutr, Peter A. N. Bosman |
| 2014 | GECCO | A novel population-based multi-objective CMA-ES and the impact of different constraint handling techniques. | Slvio Miguel Fragoso Rodrigues, Pavol Bauer, Peter A. N. Bosman |
| 2014 | GECCO | Model-based evolutionary algorithms. | Dirk Thierens, Peter A. N. Bosman |
| 2014 | PAAMS | Market Garden: A Simulation Environment for Research and User Experience in Smart Grids. | Bart Liefers, Felix Claessen, Eric J. Pauwels, Peter A. N. Bosman, Han La Poutr |
| 2014 | PPSN | Combining Model-Based EAs for Mixed-Integer Problems. | Krzysztof L. Sadowski, Dirk Thierens, Peter A. N. Bosman |
| 2013 | GECCO | More concise and robust linkage learning by filtering and combining linkage hierarchies. | Peter A. N. Bosman, Dirk Thierens |
| 2013 | GECCO | Solving satisfiability in fuzzy logics by mixing CMA-ES. | Tim Brys, Madalina M. Drugan, Peter A. N. Bosman, Martine De Cock, Ann Now |
| 2013 | GECCO | On the usefulness of linkage processing for solving MAX-SAT. | Krzysztof L. Sadowski, Peter A. N. Bosman, Dirk Thierens |
| 2013 | GECCO | Hierarchical problem solving with the linkage tree genetic algorithm. | Dirk Thierens, Peter A. N. Bosman |
| 2013 | GECCO | Model-based evolutionary algorithms. | Dirk Thierens, Peter A. N. Bosman |
| 2012 | GECCO | Incremental gaussian model-building in multi-objective EDAs with an application to deformable image registration. | Peter A. N. Bosman, Tanja Alderliesten |
| 2012 | GECCO | Linkage neighbors, optimal mixing and forced improvements in genetic algorithms. | Peter A. N. Bosman, Dirk Thierens |
| 2012 | GECCO | Predetermined versus learned linkage models. | Dirk Thierens, Peter A. N. Bosman |
| 2012 | PPSN | On Measures to Build Linkage Trees in LTGA. | Peter A. N. Bosman, Dirk Thierens |
| 2012 | PPSN | Elitist Archiving for Multi-Objective Evolutionary Algorithms: To Adapt or Not to Adapt. | Hoang N. Luong, Peter A. N. Bosman |
| 2012 | PPSN | Evolvability Analysis of the Linkage Tree Genetic Algorithm. | Dirk Thierens, Peter A. N. Bosman |
| 2011 | GECCO | The roles of local search, model building and optimal mixing in evolutionary algorithms from a bbo perspective. | Peter A. N. Bosman, Dirk Thierens |
| 2011 | GECCO | Optimal mixing evolutionary algorithms. | Dirk Thierens, Peter A. N. Bosman |
| 2010 | GECCO | The anticipated mean shift and cluster registration in mixture-based EDAs for multi-objective optimization. | Peter A. N. Bosman |
| 2010 | GECCO | Enhanced hospital resource management using anticipatory policies in online dynamic multi-objective optimization. | Anke K. Hutzschenreuter, Peter A. N. Bosman, Han La Poutr |
| 2009 | AIME | Optimization of Online Patient Scheduling with Urgencies and Preferences. | Ivan B. Vermeulen, Sander M. Boht, Peter A. N. Bosman, Sylvia G. Elkhuizen, Piet J. M. Bakker, Johannes A. La Poutr |
| 2009 | EMO | Evolutionary Multiobjective Optimization for Dynamic Hospital Resource Management. | Anke K. Hutzschenreuter, Peter A. N. Bosman, Han La Poutr |
| 2009 | GECCO | On empirical memory design, faster selection of bayesian factorizations and parameter-free gaussian EDAs. | Peter A. N. Bosman |
| 2009 | GECCO | AMaLGaM IDEAs in noiseless black-box optimization benchmarking. | Peter A. N. Bosman, Jrn Grahl, Dirk Thierens |
| 2009 | GECCO | AMaLGaM IDEAs in noisy black-box optimization benchmarking. | Peter A. N. Bosman, Jrn Grahl, Dirk Thierens |
| 2008 | PPSN | Enhancing the Performance of Maximum-Likelihood Gaussian EDAs Using Anticipated Mean Shift. | Peter A. N. Bosman, Jrn Grahl, Dirk Thierens |
| 2007 | CEC | Inventory management and the impact of anticipation in evolutionary stochastic online dynamic optimization. | Peter A. N. Bosman, Han La Poutr |
| 2007 | GECCO | SDR: a better trigger for adaptive variance scaling in normal EDAs. | Peter A. N. Bosman, Jrn Grahl, Franz Rothlauf |
| 2007 | GECCO | Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case. | Peter A. N. Bosman, Han La Poutr |
| 2007 | GECCO | Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms. | Peter A. N. Bosman, Dirk Thierens |
| 2007 | GECCO | Convergence phases, variance trajectories, and runtime analysis of continuous EDAs. | Jrn Grahl, Peter A. N. Bosman, Stefan Minner |
| 2006 | GECCO | Combining gradient techniques for numerical multi-objective evolutionary optimization. | Peter A. N. Bosman, Edwin D. de Jong |
| 2006 | GECCO | The correlation-triggered adaptive variance scaling IDEA. | Jrn Grahl, Peter A. N. Bosman, Franz Rothlauf |
| 2006 | PPSN | Computationally Intelligent Online Dynamic Vehicle Routing by Explicit Load Prediction in an Evolutionary Algorithm. | Peter A. N. Bosman, Han La Poutr |
| 2005 | EMO | The Naive MIDEA: A Baseline Multi-objective EA. | Peter A. N. Bosman, Dirk Thierens |
| 2005 | GECCO | Learning, anticipation and time-deception in evolutionary online dynamic optimization. | Peter A. N. Bosman |
| 2005 | GECCO | Evolutionary algorithms for medical simulations: a case study in minimally-invasive vascular interventions. | Peter A. N. Bosman, Tanja Alderliesten |
| 2005 | GECCO | Exploiting gradient information in numerical multi--objective evolutionary optimization. | Peter A. N. Bosman, Edwin D. de Jong |
| 2004 | PPSN | Learning Probabilistic Tree Grammars for Genetic Programming. | Peter A. N. Bosman, Edwin D. de Jong |
| 2002 | PPSN | Permutation Optimization by Iterated Estimation of Random Keys Marginal Product Factorizations. | Peter A. N. Bosman, Dirk Thierens |
| 2000 | PPSN | Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA. | Peter A. N. Bosman, Dirk Thierens |
| 1999 | GECCO | Linkage Information Processing In Distribution Estimation Algorithms. | Peter A. N. Bosman, Dirk Thierens |