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EVOW
2010
Springer
14 years 4 months ago
Parameter Tuning of Evolutionary Algorithms: Generalist vs. Specialist
Abstract. Finding appropriate parameter values for Evolutionary Algorithms (EAs) is one of the persistent challenges of Evolutionary Computing. In recent publications we showed how...
Selmar K. Smit, A. E. Eiben
GECCO
2005
Springer
130views Optimization» more  GECCO 2005»
14 years 2 months ago
Quality-time analysis of multi-objective evolutionary algorithms
A quality-time analysis of multi-objective evolutionary algorithms (MOEAs) based on schema theorem and building blocks hypothesis is developed. A bicriteria OneMax problem, a hypo...
Jian-Hung Chen, Shinn-Ying Ho, David E. Goldberg
GECCO
2004
Springer
134views Optimization» more  GECCO 2004»
14 years 2 months ago
A New Universal Cellular Automaton Discovered by Evolutionary Algorithms
In Twenty Problems in the Theory of Cellular Automata, Stephen Wolfram asks “how common computational universality and undecidability [are] in cellular automata.” This papers p...
Emmanuel Sapin, Olivier Bailleux, Jean-Jacques Cha...
IJHIS
2006
94views more  IJHIS 2006»
13 years 9 months ago
A new fine-grained evolutionary algorithm based on cellular learning automata
In this paper, a new evolutionary computing model, called CLA-EC, is proposed. This model is a combination of a model called cellular learning automata (CLA) and the evolutionary ...
Reza Rastegar, Mohammad Reza Meybodi, Arash Hariri
GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
14 years 1 months ago
On the appropriateness of evolutionary rule learning algorithms for malware detection
In this paper, we evaluate the performance of ten well-known evolutionary and non-evolutionary rule learning algorithms. The comparative study is performed on a real-world classi...
M. Zubair Shafiq, S. Momina Tabish, Muddassar Faro...