Peter A. N. Bosman

	2012
38		Peter A. N. Bosman: On Gradients and Hybrid Evolutionary Algorithms for Real-Valued Multiobjective Optimization. IEEE Trans. Evolutionary Computation 16(1): 51-69 (2012)
	2011
37		Dirk Thierens, Peter A. N. Bosman: Optimal mixing evolutionary algorithms. GECCO 2011: 617-624
36		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
35		Sara Ramezani, Peter A. N. Bosman, Han La Poutré: Adaptive Strategies for Dynamic Pricing Agents. IAT 2011: 323-328
	2010
34		Peter A. N. Bosman: The anticipated mean shift and cluster registration in mixture-based EDAs for multi-objective optimization. GECCO 2010: 351-358
33		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
32		Anke K. Hutzschenreuter, Peter A. N. Bosman, Han La Poutré: A Computational Approach to Patient Flow Logistics in Hospitals. ERCIM News 2010(81): (2010)
	2009
31		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
30		Anke K. Hutzschenreuter, Peter A. N. Bosman, Han La Poutré: Evolutionary Multiobjective Optimization for Dynamic Hospital Resource Management. EMO 2009: 320-334
29		Peter A. N. Bosman: On empirical memory design, faster selection of bayesian factorizations and parameter-free gaussian EDAs. GECCO 2009: 389-396
28		Peter A. N. Bosman, Jörn Grahl, Dirk Thierens: AMaLGaM IDEAs in noiseless black-box optimization benchmarking. GECCO (Companion) 2009: 2247-2254
27		Peter A. N. Bosman, Jörn Grahl, Dirk Thierens: AMaLGaM IDEAs in noisy black-box optimization benchmarking. GECCO (Companion) 2009: 2351-2358
	2008
26		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		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		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		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		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		Peter A. N. Bosman, Jörn Grahl, Franz Rothlauf: SDR: a better trigger for adaptive variance scaling in normal EDAs. GECCO 2007: 492-499
20		Peter A. N. Bosman, Dirk Thierens: Adaptive variance scaling in continuous multi-objective estimation-of-distribution algorithms. GECCO 2007: 500-507
19		Jörn Grahl, Peter A. N. Bosman, Stefan Minner: Convergence phases, variance trajectories, and runtime analysis of continuous EDAs. GECCO 2007: 516-522
18		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		Peter A. N. Bosman: Learning and Anticipation in Online Dynamic Optimization. Evolutionary Computation in Dynamic and Uncertain Environments 2007: 129-152
16		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		Jörn Grahl, Peter A. N. Bosman, Franz Rothlauf: The correlation-triggered adaptive variance scaling IDEA. GECCO 2006: 397-404
14		Peter A. N. Bosman, Edwin D. de Jong: Combining gradient techniques for numerical multi-objective evolutionary optimization. GECCO 2006: 627-634
13		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		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		Peter A. N. Bosman, Dirk Thierens: The Naive MIDEA: A Baseline Multi-objective EA. EMO 2005: 428-442
9		Peter A. N. Bosman, Edwin D. de Jong: Exploiting gradient information in numerical multi--objective evolutionary optimization. GECCO 2005: 755-762
8		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		Peter A. N. Bosman: Learning, anticipation and time-deception in evolutionary online dynamic optimization. GECCO Workshops 2005: 39-47
	2004
6		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		Peter A. N. Bosman, Dirk Thierens: Permutation Optimization by Iterated Estimation of Random Keys Marginal Product Factorizations. PPSN 2002: 331-340
3		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	Piet J. M. Bakker	[31]
4	Ilona Blonk-Altena	[26]
5	Sander M. Bohte	[31]
6	Sylvia G. Elkhuizen	[31]
7	Jörn Grahl	[15] [19] [21] [23] [24] [25] [27] [28]
8	Anke K. Hutzschenreuter	[26] [30] [32] [33]
9	Edwin D. de Jong	[6] [9] [14]
10	Stefan Minner	[19] [24]
11	Wiro J. Niessen	[16]
12	Johannes A. La Poutré (Han La Poutré)	[13] [18] [22] [26] [30] [31] [32] [33] [35]
13	Sara Ramezani	[35]
14	Franz Rothlauf	[15] [21]
15	Dirk Thierens	[1] [2] [3] [4] [5] [10] [12] [20] [25] [27] [28] [36] [37]
16	Ivan B. Vermeulen	[31]

Colors in the list of coauthors

Last update Sun May 27 04:04:01 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page