TY  - RPRT
A1  - Flasch, Oliver
A1  - Friese, Martina
A1  - Zaefferer, Martin
A1  - Bartz-Beielstein, Thomas
A1  - Branke, Jürgen
T1  - Learning Model-Ensemble Policies with Genetic Programming
N2  - We propose to apply typed Genetic Programming (GP) to the problem of finding surrogate-model ensembles for global optimization on compute-intensive target functions. In a model ensemble, base-models such as linear models, random forest models, or Kriging models, as well as pre- and post-processing methods, are combined. In theory, an optimal ensemble will join the strengths of its comprising base-models while avoiding their weaknesses, offering higher prediction accuracy and robustness. This study defines a grammar of model ensemble expressions and searches the set for optimal ensembles via GP. We performed an extensive experimental study based on 10 different objective functions and 2 sets of base-models. We arrive at promising results, as on unseen test data, our ensembles perform not significantly worse than the best base-model.
T3  - CIplus - 3/2015 
KW  - Modellierung
KW  - Optimierung
KW  - Ensemble Methods
KW  - Genetic Programming
KW  - Surrogate-Model-Based Optimization
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:832-cos-787
ER  - 
TY  - RPRT
A1  - Bartz-Beielstein, Thomas
A1  - Branke, Jürgen
A1  - Mehnen, Jörn
A1  - Mersmann, Olaf
T1  - Overview: Evolutionary Algorithms
N2  - Evolutionary algorithm (EA) is an umbrella term used to describe population-based stochastic direct search algorithms that in some sense mimic natural evolution. Prominent representatives of such algorithms are genetic algorithms, evolution strategies, evolutionary programming, and genetic programming. On the basis of the evolutionary cycle, similarities and differences between these algorithms are described. We briefly discuss how EAs can be adapted to work well in case of multiple objectives, and dynamic or noisy optimization problems. We look at the tuning of algorithms and present some recent developments coming from theory. Finally, typical applications of EAs to real-world problems are shown, with special emphasis on data-mining applications
T3  - CIplus - 2/2015 
KW  - Soft Computing
KW  - Versuchsplanung
KW  - Evolutionsstrategie
KW  - Evolutionärer Algorithmus
KW  - Metaheuristik
KW  - Optimierung
KW  - Optimierungsproblem
KW  - Evolutionäre Algorithmen
KW  - Evolutionsstrategien
KW  - Genetisches Programmieren
KW  - Genetische Algorithmen
KW  - Evolutionary Algorithms
KW  - Evolution Strategies
KW  - Genetic Algorithms
KW  - Genetic programming
Y1  - 2015
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:832-cos-777
ER  -