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2020 – today
- 2020
[j15]Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
On explaining machine learning models by evolving crucial and compact features. Swarm Evol. Comput. 53: 100640 (2020)- [i13]Monika Grewal, Timo M. Deist, Jan Wiersma, Peter A. N. Bosman, Tanja Alderliesten:
An End-to-end Deep Learning Approach for Landmark Detection and Matching in Medical Images. CoRR abs/2001.07434 (2020) - [i12]Arkadiy Dushatskiy, Adriënne M. Mendrik, Peter A. N. Bosman, Tanja Alderliesten:
Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms. CoRR abs/2001.08552 (2020) - [i11]Marco Virgolin, Ziyuan Wang, B. V. Balgobind, I. W. E. M. van Dijk, Jan Wiersma, P. S. Kroon, G. O. Janssens, Marcel van Herk, D. C. Hodgson, L. Zadravec Zaletel, C. R. N. Rasch, Arjan Bel, Peter A. N. Bosman, Tanja Alderliesten:
Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy. CoRR abs/2002.07161 (2020) - [i10]S. C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Uncrowded Hypervolume-based Multi-objective Optimization with Gene-pool Optimal Mixing. CoRR abs/2004.05068 (2020) - [i9]T. Den Ottelander, Arkadiy Dushatskiy, Marco Virgolin, Peter A. N. Bosman:
Local Search is a Remarkably Strong Baseline for Neural Architecture Search. CoRR abs/2004.08996 (2020)
2010 – 2019
- 2019
- [j14]Kleopatra Pirpinia, Peter A. N. Bosman, Jan-Jakob Sonke
, Marcel van Herk, Tanja Alderliesten:
Evolutionary Machine Learning for Multi-Objective Class Solutions in Medical Deformable Image Registration. Algorithms 12(5): 99 (2019) - [j13]Ngoc Hoang Luong, Tanja Alderliesten, Bradley R. Pieters, Arjan Bel, Yury Niatsetski, Peter A. N. Bosman:
Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy. Appl. Soft Comput. 84 (2019) - [c88]S. C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Real-valued evolutionary multi-modal multi-objective optimization by hill-valley clustering. GECCO 2019: 568-576 - [c87]Arkadiy Dushatskiy, Adriënne M. Mendrik, Tanja Alderliesten, Peter A. N. Bosman:
Convolutional neural network surrogate-assisted GOMEA. GECCO 2019: 753-761 - [c86]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms. GECCO (Companion) 2019: 806-836 - [c85]Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
Linear scaling with and within semantic backpropagation-based genetic programming for symbolic regression. GECCO 2019: 1084-1092 - [c84]Erik A. Meulman, Peter A. N. Bosman:
Toward self-learning model-based EAs. GECCO (Companion) 2019: 1495-1503 - [c83]Kleopatra Pirpinia, Peter A. N. Bosman, Jan-Jakob Sonke, Marcel van Herk, Tanja Alderliesten:
Evolutionary multi-objective meta-optimization of deformation and tissue removal parameters improves the performance of deformable image registration of pre- and post-surgery images. Medical Imaging: Image Processing 2019: 1094939 - [i8]Marco Virgolin, Tanja Alderliesten, Cees Witteveen, Peter A. N. Bosman:
A Model-based Genetic Programming Approach for Symbolic Regression of Small Expressions. CoRR abs/1904.02050 (2019) - [i7]Marco Virgolin, Tanja Alderliesten, Peter A. N. Bosman:
On Explaining Machine Learning Models by Evolving Crucial and Compact Features. CoRR abs/1907.02260 (2019) - [i6]S. C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Benchmarking HillVallEA for the GECCO 2019 Competition on Multimodal Optimization. CoRR abs/1907.10988 (2019) - [i5]Marco Virgolin, Ziyuan Wang, Tanja Alderliesten, Peter A. N. Bosman:
Machine learning for automatic construction of pseudo-realistic pediatric abdominal phantoms. CoRR abs/1909.03723 (2019) - 2018
- [j12]Krzysztof L. Sadowski, Dirk Thierens, Peter A. N. Bosman:
GAMBIT: A Parameterless Model-Based Evolutionary Algorithm for Mixed-Integer Problems. Evol. Comput. 26(1) (2018) - [j11]Ngoc Hoang Luong, Han La Poutré, Peter A. N. Bosman:
Exploiting Linkage Information and Problem-Specific Knowledge in Evolutionary Distribution Network Expansion Planning. Evol. Comput. 26(3) (2018) - [j10]Eric Medvet, Marco Virgolin, Mauro Castelli, Peter A. N. Bosman, Ivo Gonçalves, Tea Tusar:
Unveiling evolutionary algorithm representation with DU maps. Genetic Programming and Evolvable Machines 19(3): 351-389 (2018) - [j9]Peter A. N. Bosman, Marcus Gallagher:
The importance of implementation details and parameter settings in black-box optimization: a case study on Gaussian estimation-of-distribution algorithms and circles-in-a-square packing problems. Soft Comput. 22(4): 1209-1223 (2018) - [j8]Ngoc Hoang Luong, Tanja Alderliesten, Arjan Bel, Yury Niatsetski, Peter A. N. Bosman:
Application and benchmarking of multi-objective evolutionary algorithms on high-dose-rate brachytherapy planning for prostate cancer treatment. Swarm Evol. Comput. 40: 37-52 (2018) - [j7]Ngoc Hoang Luong, Han La Poutré, Peter A. N. Bosman:
Multi-objective Gene-pool Optimal Mixing Evolutionary Algorithm with the Interleaved Multi-start Scheme. Swarm Evol. Comput. 40: 238-254 (2018) - [c82]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms: GECCO 2018 tutorial. GECCO (Companion) 2018: 553-583 - [c81]S. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman:
Real-valued evolutionary multi-modal optimization driven by hill-valley clustering. GECCO 2018: 857-864 - [c80]Anton Bouter, Tanja Alderliesten, Arjan Bel, Cees Witteveen, Peter A. N. Bosman:
Large-scale parallelization of partial evaluations in evolutionary algorithms for real-world problems. GECCO 2018: 1199-1206 - [c79]Marjolein C. van der Meer, Bradley R. Pieters, Yury Niatsetski, Tanja Alderliesten, Arjan Bel, Peter A. N. Bosman:
Better and faster catheter position optimization in HDR brachytherapy for prostate cancer using multi-objective real-valued GOMEA. GECCO 2018: 1387-1394 - [c78]Marco Virgolin, Tanja Alderliesten, Arjan Bel, Cees Witteveen, Peter A. N. Bosman:
Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors. GECCO 2018: 1395-1402 - [c77]G. H. Aalvanger, Ngoc Hoang Luong, Peter A. N. Bosman, Dirk Thierens:
Heuristics in Permutation GOMEA for Solving the Permutation Flowshop Scheduling Problem. PPSN (1) 2018: 146-157 - [i4]S. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman:
Benchmarking the Hill-Valley Evolutionary Algorithm for the GECCO 2018 Competition on Niching Methods Multimodal Optimization. CoRR abs/1807.00188 (2018) - [i3]S. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman:
Real-Valued Evolutionary Multi-Modal Optimization driven by Hill-Valley Clustering. CoRR abs/1810.07085 (2018) - 2017
- [c76]Anton Bouter, Ngoc Hoang Luong, Cees Witteveen, Tanja Alderliesten, Peter A. N. Bosman:
The multi-objective real-valued gene-pool optimal mixing evolutionary algorithm. GECCO 2017: 537-544 - [c75]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms: GECCO 2017 tutorial. GECCO (Companion) 2017: 545-575 - [c74]Anton Bouter, Tanja Alderliesten, Cees Witteveen, Peter A. N. Bosman:
Exploiting linkage information in real-valued optimization with the real-valued gene-pool optimal mixing evolutionary algorithm. GECCO 2017: 705-712 - [c73]S. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman:
Niching an estimation-of-distribution algorithm by hierarchical Gaussian mixture learning. GECCO 2017: 713-720 - [c72]Marco Virgolin, Tanja Alderliesten, Cees Witteveen, Peter A. N. Bosman:
Scalable genetic programming by gene-pool optimal mixing and input-space entropy-based building-block learning. GECCO 2017: 1041-1048 - [c71]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:
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. GECCO 2017: 1224-1231 - [c70]Ngoc Hoang Luong, Anton Bouter, Marjolein C. van der Meer, Yury Niatsetski, Cees Witteveen, Arjan Bel, Tanja Alderliesten, Peter A. N. Bosman:
Efficient, effective, and insightful tackling of the high-dose-rate brachytherapy treatment planning problem for prostate cancer using evolutionary multi-objective optimization algorithms. GECCO (Companion) 2017: 1372-1379 - [c69]Anton Bouter, Kleopatra Pirpinia, Tanja Alderliesten, Peter A. N. Bosman:
Spatial redistribution of irregularly-spaced pareto fronts for more intuitive navigation and solution selection. GECCO (Companion) 2017: 1697-1704 - [c68]Anton Bouter, Tanja Alderliesten, Peter A. N. Bosman:
A novel model-based evolutionary algorithm for multi-objective deformable image registration with content mismatch and large deformations: benchmarking efficiency and quality. Medical Imaging: Image Processing 2017: 1013312 - [e2]Peter A. N. Bosman:
Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2017, Berlin, Germany, July 15-19, 2017. ACM 2017, ISBN 978-1-4503-4920-8 [contents] - [e1]Peter A. N. Bosman:
Genetic and Evolutionary Computation Conference, Berlin, Germany, July 15-19, 2017, Companion Material Proceedings. ACM 2017, ISBN 978-1-4503-4939-0 [contents] - 2016
- [c67]Krzysztof L. Sadowski, Peter A. N. Bosman, Dirk Thierens:
Learning and exploiting mixed variable dependencies with a model-based EA. CEC 2016: 4382-4389 - [c66]Dirk Thierens, Peter A. N. Bosman:
Model-Based Evolutionary Algorithms. GECCO (Companion) 2016: 385-412 - [c65]Peter A. N. Bosman, Ngoc Hoang Luong, Dirk Thierens:
Expanding from Discrete Cartesian to Permutation Gene-pool Optimal Mixing Evolutionary Algorithms. GECCO 2016: 637-644 - [c64]Peter A. N. Bosman, John A. W. McCall:
GECCO'16 Model-Based Evolutionary Algorithms (MBEA) Workshop Chairs' Welcome. GECCO (Companion) 2016: 1401 - [c63]Kleopatra Pirpinia, Peter A. N. Bosman, Jan-Jakob Sonke, Marcel van Herk, Tanja Alderliesten:
A first step toward uncovering the truth about weight tuning in deformable image registration. Medical Imaging: Image Processing 2016: 978445 - [c62]Peter A. N. Bosman, Tanja Alderliesten:
Smart grid initialization reduces the computational complexity of multi-objective image registration based on a dual-dynamic transformation model to account for large anatomical differences. Medical Imaging: Image Processing 2016: 978447 - [c61]Willem den Besten, Dirk Thierens, Peter A. N. Bosman:
The Multiple Insertion Pyramid: A Fast Parameter-Less Population Scheme. PPSN 2016: 48-58 - 2015
- [c60]Dirk Thierens, Peter A. N. Bosman:
Model-Based Evolutionary Algorithms. GECCO (Companion) 2015: 93-120 - [c59]Krzysztof L. Sadowski, Peter A. N. Bosman, Dirk Thierens:
A Clustering-Based Model-Building EA for Optimization Problems with Binary and Real-Valued Variables. GECCO 2015: 911-918 - [c58]Ngoc Hoang Luong, Han La Poutré, Peter A. N. Bosman:
Exploiting Linkage Information and Problem-Specific Knowledge in Evolutionary Distribution Network Expansion Planning. GECCO 2015: 1231-1238 - [c57]Kleopatra Pirpinia, Tanja Alderliesten, Jan-Jakob Sonke, Marcel van Herk, Peter A. N. Bosman:
Diversifying Multi-Objective Gradient Techniques and their Role in Hybrid Multi-Objective Evolutionary Algorithms for Deformable Medical Image Registration. GECCO 2015: 1255-1262 - [c56]Roy de Bokx, Dirk Thierens, Peter A. N. Bosman:
In Search of Optimal Linkage Trees. GECCO (Companion) 2015: 1375-1376 - [c55]Tanja Alderliesten, Peter A. N. Bosman, Arjan Bel:
Getting the most out of additional guidance information in deformable image registration by leveraging multi-objective optimization. Medical Imaging: Image Processing 2015: 94131R - [c54]Kleopatra Pirpinia, Peter A. N. Bosman, Jan-Jakob Sonke, Marcel van Herk, Tanja Alderliesten:
On the usefulness of gradient information in multi-objective deformable image registration using a B-spline-based dual-dynamic transformation model: comparison of three optimization algorithms. Medical Imaging: Image Processing 2015: 941339 - 2014
- [c53]Ngoc Hoang Luong, Han La Poutré, Peter A. N. Bosman:
Multi-objective gene-pool optimal mixing evolutionary algorithms. GECCO 2014: 357-364 - [c52]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms. GECCO (Companion) 2014: 431-458 - [c51]Sílvio Miguel Fragoso Rodrigues, Pavol Bauer, Peter A. N. Bosman:
A novel population-based multi-objective CMA-ES and the impact of different constraint handling techniques. GECCO 2014: 991-998 - [c50]Ngoc Hoang Luong, Marinus O. W. Grond, Han La Poutré, Peter A. N. Bosman:
Efficiency enhancements for evolutionary capacity planning in distribution grids. GECCO (Companion) 2014: 1189-1196 - [c49]Tanja Alderliesten, Peter A. N. Bosman, Jan-Jakob Sonke, Arjan Bel:
A multi-resolution strategy for a multi-objective deformable image registration framework that accommodates large anatomical differences. Medical Imaging: Image Processing 2014: 90343G - [c48]Bart Liefers, Felix Claessen, Eric J. Pauwels, Peter A. N. Bosman, Han La Poutré:
Market Garden: A Simulation Environment for Research and User Experience in Smart Grids. PAAMS 2014: 351-354 - [c47]Krzysztof L. Sadowski, Dirk Thierens, Peter A. N. Bosman:
Combining Model-Based EAs for Mixed-Integer Problems. PPSN 2014: 342-351 - [c46]Marinus O. W. Grond, Ngoc Hoang Luong, Johan Morren, Peter A. N. Bosman, Han Slootweg, Han La Poutré:
Practice-oriented optimization of distribution network planning using metaheuristic algorithms. PSCC 2014: 1-8 - 2013
- [j6]Peter A. N. Bosman, Jörn Grahl, Dirk Thierens:
Benchmarking Parameter-Free AMaLGaM on Functions With and Without Noise. Evol. Comput. 21(3): 445-469 (2013) - [c45]Hoang N. Luong, Marinus O. W. Grond, Peter A. N. Bosman, Han La Poutré:
Medium-Voltage Distribution Network Expansion Planning with Gene-pool Optimal Mixing Evolutionary Algorithms. Artificial Evolution 2013: 93-105 - [c44]Peter A. N. Bosman, Dirk Thierens:
More concise and robust linkage learning by filtering and combining linkage hierarchies. GECCO 2013: 359-366 - [c43]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms. GECCO (Companion) 2013: 377-404 - [c42]Krzysztof L. Sadowski, Peter A. N. Bosman, Dirk Thierens:
On the usefulness of linkage processing for solving MAX-SAT. GECCO 2013: 853-860 - [c41]Dirk Thierens, Peter A. N. Bosman:
Hierarchical problem solving with the linkage tree genetic algorithm. GECCO 2013: 877-884 - [c40]Tim Brys, Madalina M. Drugan, Peter A. N. Bosman, Martine De Cock, Ann Nowé:
Solving satisfiability in fuzzy logics by mixing CMA-ES. GECCO 2013: 1125-1132 - [c39]Tim Brys, Madalina M. Drugan, Peter A. N. Bosman, Martine De Cock, Ann Nowé:
Local search and restart strategies for satisfiability solving in fuzzy logics. GEFS 2013: 52-59 - [c38]Tanja Alderliesten, Jan-Jakob Sonke, Peter A. N. Bosman:
Deformable image registration by multi-objective optimization using a dual-dynamic transformation model to account for large anatomical differences. Medical Imaging: Image Processing 2013: 866910 - [i2]Felix Claessen, Nicolas Höning, Bart Liefers, Han La Poutré, Peter A. N. Bosman:
Market Garden: A Scalable Research Environment for Heterogeneous Electricity Markets. ERCIM News 2013(92) (2013) - 2012
- [j5]Peter A. N. Bosman:
On Gradients and Hybrid Evolutionary Algorithms for Real-Valued Multiobjective Optimization. IEEE Trans. Evol. Comput. 16(1): 51-69 (2012) - [c37]Peter A. N. Bosman, Tanja Alderliesten:
Incremental gaussian model-building in multi-objective EDAs with an application to deformable image registration. GECCO 2012: 241-248 - [c36]Dirk Thierens, Peter A. N. Bosman:
Predetermined versus learned linkage models. GECCO 2012: 289-296 - [c35]Peter A. N. Bosman, Dirk Thierens:
Linkage neighbors, optimal mixing and forced improvements in genetic algorithms. GECCO 2012: 585-592 - [c34]Dirk Thierens, Peter A. N. Bosman:
Learning the Neighborhood with the Linkage Tree Genetic Algorithm. LION 2012: 491-496 - [c33]Tanja Alderliesten, Jan-Jakob Sonke, Peter A. N. Bosman:
Multi-objective optimization for deformable image registration: proof of concept. Medical Imaging: Image Processing 2012: 831420 - [c32]Hoang N. Luong, Peter A. N. Bosman:
Elitist Archiving for Multi-Objective Evolutionary Algorithms: To Adapt or Not to Adapt. PPSN (2) 2012: 72-81 - [c31]Peter A. N. Bosman, Dirk Thierens:
On Measures to Build Linkage Trees in LTGA. PPSN (1) 2012: 276-285 - [c30]Dirk Thierens, Peter A. N. Bosman:
Evolvability Analysis of the Linkage Tree Genetic Algorithm. PPSN (1) 2012: 286-295 - 2011
- [c29]Dirk Thierens, Peter A. N. Bosman:
Optimal mixing evolutionary algorithms. GECCO 2011: 617-624 - [c28]Peter A. N. Bosman, Dirk Thierens:
The roles of local search, model building and optimal mixing in evolutionary algorithms from a bbo perspective. GECCO (Companion) 2011: 663-670 - [c27]Sara Ramezani, Peter A. N. Bosman, Han La Poutré:
Adaptive Strategies for Dynamic Pricing Agents. IAT 2011: 323-328 - 2010
- [c26]Peter A. N. Bosman:
The anticipated mean shift and cluster registration in mixture-based EDAs for multi-objective optimization. GECCO 2010: 351-358 - [c25]Anke K. Hutzschenreuter, Peter A. N. Bosman, Han La Poutré:
Enhanced hospital resource management using anticipatory policies in online dynamic multi-objective optimization. GECCO 2010: 541-542 - [i1]Anke K. Hutzschenreuter, Peter A. N. Bosman, Han La Poutré:
A Computational Approach to Patient Flow Logistics in Hospitals. ERCIM News 2010(81) (2010)
2000 – 2009
- 2009
- [c24]Ivan B. Vermeulen, Sander M. Bohte, Peter A. N. Bosman, Sylvia G. Elkhuizen, Piet J. M. Bakker, Johannes A. La Poutré:
Optimization of Online Patient Scheduling with Urgencies and Preferences. AIME 2009: 71-80 - [c23]Anke K. Hutzschenreuter, Peter A. N. Bosman, Han La Poutré:
Evolutionary Multiobjective Optimization for Dynamic Hospital Resource Management. EMO 2009: 320-334 - [c22]Peter A. N. Bosman:
On empirical memory design, faster selection of bayesian factorizations and parameter-free gaussian EDAs. GECCO 2009: 389-396 - [c21]Peter A. N. Bosman, Jörn Grahl, Dirk Thierens:
AMaLGaM IDEAs in noiseless black-box optimization benchmarking. GECCO (Companion) 2009: 2247-2254 - [c20]Peter A. N. Bosman, Jörn Grahl, Dirk Thierens:
AMaLGaM IDEAs in noisy black-box optimization benchmarking. GECCO (Companion) 2009: 2351-2358 - 2008
- [j4]Peter A. N. Bosman, Jörn Grahl:
Matching inductive search bias and problem structure in continuous Estimation-of-Distribution Algorithms. Eur. J. Oper. Res. 185(3): 1246-1264 (2008) - [c19]Anke K. Hutzschenreuter, Peter A. N. Bosman, Ilona Blonk-Altena, Jan van Aarle, Han La Poutré:
Agent-based patient admission scheduling in hospitals. AAMAS (Industry Track) 2008: 45-52 - [c18]Peter A. N. Bosman, Jörn Grahl, Dirk Thierens:
Enhancing the Performance of Maximum-Likelihood Gaussian EDAs Using Anticipated Mean Shift. PPSN 2008: 133-143 - [p4]Jörn Grahl, Stefan Minner, Peter A. N. Bosman:
Learning Structure Illuminates Black Boxes - An Introduction to Estimation of Distribution Algorithms. Advances in Metaheuristics for Hard Optimization 2008: 365-395 - 2007
- [j3]Tanja Alderliesten, Peter A. N. Bosman, Wiro J. Niessen:
Towards a Real-Time Minimally-Invasive Vascular Intervention Simulation System. IEEE Trans. Med. Imaging 26(1): 128-132 (2007) - [c17]Peter A. N. Bosman, Han La Poutré:
Inventory management and the impact of anticipation in evolutionary stochastic online dynamic optimization. IEEE Congress on Evolutionary Computation 2007: 268-275 - [c16]Peter A. N. Bosman, Jörn Grahl, Franz Rothlauf:
SDR: a better trigger for adaptive variance scaling in normal EDAs. GECCO 2007: 492-499 - [c15]Peter A. N. Bosman, Dirk Thierens:
Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms. GECCO 2007: 500-507 - [c14]Jörn Grahl, Peter A. N. Bosman, Stefan Minner:
Convergence phases, variance trajectories, and runtime analysis of continuous EDAs. GECCO 2007: 516-522 - [c13]Peter A. N. Bosman, Han La Poutré:
Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case. GECCO 2007: 1165-1172 - [p3]Peter A. N. Bosman:
Learning and Anticipation in Online Dynamic Optimization. Evolutionary Computation in Dynamic and Uncertain Environments 2007: 129-152 - 2006
- [c12]Jörn Grahl, Peter A. N. Bosman, Franz Rothlauf:
The correlation-triggered adaptive variance scaling IDEA. GECCO 2006: 397-404 - [c11]Peter A. N. Bosman, Edwin D. de Jong:
Combining gradient techniques for numerical multi-objective evolutionary optimization. GECCO 2006: 627-634 - [c10]Peter A. N. Bosman, Han La Poutré:
Computationally Intelligent Online Dynamic Vehicle Routing by Explicit Load Prediction in an Evolutionary Algorithm. PPSN 2006: 312-321 - [p2]Peter A. N. Bosman, Dirk Thierens:
Multi-objective Optimization with the Naive $$ \mathbb{M} $$ ID $$ \mathbb{E} $$ A. Towards a New Evolutionary Computation 2006: 123-157 - [p1]Peter A. N. Bosman, Dirk Thierens:
Numerical Optimization with Real-Valued Estimation-of-Distribution Algorithms. Scalable Optimization via Probabilistic Modeling 2006: 91-120 - 2005
- [c9]Peter A. N. Bosman:
Learning, Anticipation and Time-Deception in Evolutionary Online Dynamic Optimization. BNAIC 2005: 321-322 - [c8]Peter A. N. Bosman, Dirk Thierens:
The Naive MIDEA: A Baseline Multi-objective EA. EMO 2005: 428-442 - [c7]Peter A. N. Bosman:
Learning, anticipation and time-deception in evolutionary online dynamic optimization. GECCO Workshops 2005: 39-47 - [c6]Peter A. N. Bosman, Tanja Alderliesten:
Evolutionary algorithms for medical simulations: a case study in minimally-invasive vascular interventions. GECCO Workshops 2005: 125-132 - [c5]Peter A. N. Bosman, Edwin D. de Jong:
Exploiting gradient information in numerical multi--objective evolutionary optimization. GECCO 2005: 755-762 - 2004
- [c4]Peter A. N. Bosman, Edwin D. de Jong:
Learning Probabilistic Tree Grammars for Genetic Programming. PPSN 2004: 192-201 - 2003
- [j2]Peter A. N. Bosman, Dirk Thierens:
The balance between proximity and diversity in multiobjective evolutionary algorithms. IEEE Trans. Evol. Comput. 7(2): 174-188 (2003) - 2002
- [j1]Peter A. N. Bosman, Dirk Thierens:
Multi-objective optimization with diversity preserving mixture-based iterated density estimation evolutionary algorithms. Int. J. Approx. Reason. 31(3): 259-289 (2002) - [c3]Peter A. N. Bosman, Dirk Thierens:
Permutation Optimization by Iterated Estimation of Random Keys Marginal Product Factorizations. PPSN 2002: 331-340 - 2000
- [c2]