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Semantic ScholarPeter A. N. Bosman
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2010 – today
- 2018
[j11]Krzysztof L. Sadowski, Dirk Thierens, Peter A. N. Bosman:
GAMBIT: A Parameterless Model-Based Evolutionary Algorithm for Mixed-Integer Problems. Evolutionary Computation 26(1) (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 and Evolutionary Computation 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 and Evolutionary Computation 40: 238-254 (2018) - [c81]Dirk Thierens, Peter A. N. Bosman:
Model-based evolutionary algorithms: GECCO 2018 tutorial. GECCO (Companion) 2018: 553-583 - [c80]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 - [c79]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 - [c78]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 - [c77]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 - [i3]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) - 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. Evolutionary Computation 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. Evolutionary Computation 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]
- [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]
- [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. European Journal of Operational Research 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 - [p3]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 - [p2]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 - [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. Evolutionary Computation 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. Reasoning 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]Peter A. N. Bosman, Dirk Thierens:
Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA. PPSN 2000: 767-776
1990 – 1999
- 1999
- [c1]Peter A. N. Bosman, Dirk Thierens:
Linkage Information Processing In Distribution Estimation Algorithms. GECCO 1999: 60-67
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