Peter A. N. Bosman

2009
27	EE	Anke K. Hutzschenreuter, Peter A. N. Bosman, Han La Poutré: Evolutionary Multiobjective Optimization for Dynamic Hospital Resource Management. EMO 2009: 320-334
2008
26	EE	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
25	EE	Peter A. N. Bosman, Jörn Grahl, Dirk Thierens: Enhancing the Performance of Maximum-Likelihood Gaussian EDAs Using Anticipated Mean Shift. PPSN 2008: 133-143
24	EE	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
23	EE	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)
2007
22	EE	Peter A. N. Bosman, Han La Poutré: Learning and anticipation in online dynamic optimization with evolutionary algorithms: the stochastic case. GECCO 2007: 1165-1172
21	EE	Peter A. N. Bosman, Jörn Grahl, Franz Rothlauf: SDR: a better trigger for adaptive variance scaling in normal EDAs. GECCO 2007: 492-499
20	EE	Peter A. N. Bosman, Dirk Thierens: Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms. GECCO 2007: 500-507
19	EE	Jörn Grahl, Peter A. N. Bosman, Stefan Minner: Convergence phases, variance trajectories, and runtime analysis of continuous EDAs. GECCO 2007: 516-522
18	EE	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
17	EE	Peter A. N. Bosman: Learning and Anticipation in Online Dynamic Optimization. Evolutionary Computation in Dynamic and Uncertain Environments 2007: 129-152
16	EE	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)
2006
15	EE	Jörn Grahl, Peter A. N. Bosman, Franz Rothlauf: The correlation-triggered adaptive variance scaling IDEA. GECCO 2006: 397-404
14	EE	Peter A. N. Bosman, Edwin D. de Jong: Combining gradient techniques for numerical multi-objective evolutionary optimization. GECCO 2006: 627-634
13	EE	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
12	EE	Peter A. N. Bosman, Dirk Thierens: Numerical Optimization with Real-Valued Estimation-of-Distribution Algorithms. Scalable Optimization via Probabilistic Modeling 2006: 91-120
2005
11		Peter A. N. Bosman: Learning, Anticipation and Time-Deception in Evolutionary Online Dynamic Optimization. BNAIC 2005: 321-322
10	EE	Peter A. N. Bosman, Dirk Thierens: The Naive MIDEA: A Baseline Multi-objective EA. EMO 2005: 428-442
9	EE	Peter A. N. Bosman, Edwin D. de Jong: Exploiting gradient information in numerical multi--objective evolutionary optimization. GECCO 2005: 755-762
8	EE	Peter A. N. Bosman, Tanja Alderliesten: Evolutionary algorithms for medical simulations: a case study in minimally-invasive vascular interventions. GECCO Workshops 2005: 125-132
7	EE	Peter A. N. Bosman: Learning, anticipation and time-deception in evolutionary online dynamic optimization. GECCO Workshops 2005: 39-47
2004
6	EE	Peter A. N. Bosman, Edwin D. de Jong: Learning Probabilistic Tree Grammars for Genetic Programming. PPSN 2004: 192-201
2003
5		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
4	EE	Peter A. N. Bosman, Dirk Thierens: Permutation Optimization by Iterated Estimation of Random Keys Marginal Product Factorizations. PPSN 2002: 331-340
3	EE	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)
2000
2		Peter A. N. Bosman, Dirk Thierens: Expanding from Discrete to Continuous Estimation of Distribution Algorithms: The IDEA. PPSN 2000: 767-776
1999
1		Peter A. N. Bosman, Dirk Thierens: Linkage Information Processing In Distribution Estimation Algorithms. GECCO 1999: 60-67

Coauthor Index

1	Jan van Aarle	[26]
2	Tanja Alderliesten	[8] [16]
3	Ilona Blonk-Altena	[26]
4	Jörn Grahl	[15] [19] [21] [23] [24] [25]
5	Anke K. Hutzschenreuter	[26] [27]
6	Edwin D. de Jong	[6] [9] [14]
7	Stefan Minner	[19] [24]
8	Wiro J. Niessen	[16]
9	Johannes A. La Poutré (Han La Poutré)	[13] [18] [22] [26] [27]
10	Franz Rothlauf	[15] [21]
11	Dirk Thierens	[1] [2] [3] [4] [5] [10] [12] [20] [25]

Colors in the list of coauthors