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» On the Brittleness of Evolutionary Algorithms
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GECCO
2009
Springer
167views Optimization» more  GECCO 2009»
14 years 3 months ago
Fixed-parameter evolutionary algorithms and the vertex cover problem
In this paper, we consider multi-objective evolutionary algorithms for the Vertex Cover problem in the context of parameterized complexity. We relate the runtime of our algorithms...
Stefan Kratsch, Frank Neumann
GECCO
2005
Springer
108views Optimization» more  GECCO 2005»
14 years 2 months ago
Some theoretical results about the computation time of evolutionary algorithms
This paper focuses on the computation time of evolutionary algorithms. First, some exact expressions of the mean first hitting times of general evolutionary algorithms in finite...
Lixin X. Ding, Jinghu Yu
GECCO
2006
Springer
137views Optimization» more  GECCO 2006»
14 years 7 days ago
A method for parameter calibration and relevance estimation in evolutionary algorithms
We present and evaluate a method for estimating the relevance and calibrating the values of parameters of an evolutionary algorithm. The method provides an information theoretic m...
Volker Nannen, A. E. Eiben
GECCO
2004
Springer
14 years 2 months ago
Towards a Generally Applicable Self-Adapting Hybridization of Evolutionary Algorithms
When applied to real-world problems, the powerful optimization tool of Evolutionary Algorithms frequently turns out to be too time-consuming due to elaborate fitness calculations t...
Wilfried Jakob, Christian Blume, Georg Bretthauer
CEC
2010
IEEE
13 years 9 months ago
Evolutionary multi-objective optimization algorithms with probabilistic representation based on pheromone trails
Abstract-- Recently, the research on quantum-inspired evolutionary algorithms (QEA) has attracted some attention in the area of evolutionary computation. QEA use a probabilistic re...
Hui Li, Dario Landa Silva, Xavier Gandibleux