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GECCO
2008
Springer
156views Optimization» more  GECCO 2008»
13 years 6 months ago
Computing minimum cuts by randomized search heuristics
We study the minimum s-t-cut problem in graphs with costs on the edges in the context of evolutionary algorithms. Minimum cut problems belong to the class of basic network optimiz...
Frank Neumann, Joachim Reichel, Martin Skutella
KES
2008
Springer
13 years 4 months ago
Instruction-based development: From evolution to generic structures of digital circuits
Evolutionary techniques provide powerful tools to design novel solutions for hard problems in different areas. However, the problem of scale (i.e. how to create a large, complex s...
Michal Bidlo, Jaroslav Skarvada
GECCO
2007
Springer
167views Optimization» more  GECCO 2007»
13 years 11 months ago
Computational complexity and evolutionary computation
Thomas Jansen, Frank Neumann
ARTMED
2002
121views more  ARTMED 2002»
13 years 4 months ago
An evolutionary artificial neural networks approach for breast cancer diagnosis
This paper presents an evolutionary artificial neural network approach based on the pareto differential evolution algorithm augmented with local search for the prediction of breas...
Hussein A. Abbass
GECCO
2006
Springer
220views Optimization» more  GECCO 2006»
13 years 8 months ago
Comparing evolutionary algorithms on the problem of network inference
In this paper, we address the problem of finding gene regulatory networks from experimental DNA microarray data. We focus on the evaluation of the performance of different evoluti...
Christian Spieth, Rene Worzischek, Felix Streicher...