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GECCO
2004
Springer
102views Optimization» more  GECCO 2004»
14 years 23 days ago
Dynamic and Scalable Evolutionary Data Mining: An Approach Based on a Self-Adaptive Multiple Expression Mechanism
Data mining has recently attracted attention as a set of efficient techniques that can discover patterns from huge data. More recent advancements in collecting massive evolving da...
Olfa Nasraoui, Carlos Rojas, Cesar Cardona
CEC
2007
IEEE
14 years 1 months ago
Towards a generic control strategy for Evolutionary Algorithms: an adaptive fuzzy-learning approach
— This paper presents a new method to generalize strategies in order to control parameters of Evolutionary Algorithms (EAs). A learning process establishes the relationship betwe...
Jorge Maturana, Frédéric Saubion
GECCO
2009
Springer
14 years 1 months ago
Dynamic evolutionary optimisation: an analysis of frequency and magnitude of change
In this paper, we rigorously analyse how the magnitude and frequency of change may affect the performance of the algorithm (1+1) EAdyn on a set of artificially designed pseudo-Bo...
Philipp Rohlfshagen, Per Kristian Lehre, Xin Yao
EMO
2001
Springer
150views Optimization» more  EMO 2001»
13 years 12 months ago
On the Effects of Archiving, Elitism, and Density Based Selection in Evolutionary Multi-objective Optimization
This paper studies the influence of what are recognized as key issues in evolutionary multi-objective optimization: archiving (to keep track of the current non-dominated solutions...
Marco Laumanns, Eckart Zitzler, Lothar Thiele
GECCO
2005
Springer
108views Optimization» more  GECCO 2005»
14 years 27 days 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