Günter Rudolph

Name: dblp XML data dump
Creator: Schloss Dagstuhl - Leibniz Center for Informatics
Published: 1993
License: https://creativecommons.org/publicdomain/zero/1.0/
Keywords: dblp, XML, computer science, scholarly publications, metadata

◀ ▶ joint publications with Nicola Beume

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Publications

2011
[c43]
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Nicola Beume, Marco Laumanns, Günter Rudolph:
Convergence rates of SMS-EMOA on continuous bi-objective problem classes. FOGA 2011: 243-252
2010
[c35]
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Nicola Beume, Marco Laumanns, Günter Rudolph:
Convergence Rates of (1+1) Evolutionary Multiobjective Optimization Algorithms. PPSN (1) 2010: 597-606
[c34]
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  - conf/ppsn/WessingBRN10
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Simon Wessing, Nicola Beume, Günter Rudolph, Boris Naujoks:
Parameter Tuning Boosts Performance of Variation Operators in Multiobjective Optimization. PPSN (1) 2010: 728-737
2009
[c31]
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  - conf/emo/BeumeNPRW09
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Nicola Beume, Boris Naujoks, Mike Preuss, Günter Rudolph, Tobias Wagner:
Effects of 1-Greedy -Metric-Selection on Innumerably Large Pareto Fronts. EMO 2009: 21-35
[c30]
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  - conf/gecco/KochKRB09
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Patrick Koch, Oliver Kramer, Günter Rudolph, Nicola Beume:
On the hybridization of SMS-EMOA and local search for continuous multiobjective optimization. GECCO 2009: 603-610
2008
[j11]
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Nicola Beume, Boris Naujoks, Günter Rudolph:
SMS-EMOA - Effektive evolutionäre Mehrzieloptimierung (SMS-EMOA - Effective Evolutionary Multiobjective Optimization). Autom. 56(7): 357-364 (2008)
[c27]
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  - conf/cec/VossBRI08
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Thomas Voß, Nicola Beume, Günter Rudolph, Christian Igel:
Scalarization versus indicator-based selection in multi-objective CMA evolution strategies. IEEE Congress on Evolutionary Computation 2008: 3036-3043
[e4]
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Günter Rudolph, Thomas Jansen, Simon M. Lucas, Carlo Poloni, Nicola Beume:
Parallel Problem Solving from Nature - PPSN X, 10th International Conference Dortmund, Germany, September 13-17, 2008, Proceedings. Lecture Notes in Computer Science 5199, Springer 2008, ISBN 978-3-540-87699-1 [contents]
2006
[c19]
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Nicola Beume, Günter Rudolph:
Faster s-metric calculation by considering dominated hypervolume as klee's measure problem. Computational Intelligence 2006: 233-238

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