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GECCO
2009
Springer
124views Optimization» more  GECCO 2009»
15 years 11 months ago
Three interconnected parameters for genetic algorithms
When an optimization problem is encoded using genetic algorithms, one must address issues of population size, crossover and mutation operators and probabilities, stopping criteria...
Pedro A. Diaz-Gomez, Dean F. Hougen
GECCO
2009
Springer
144views Optimization» more  GECCO 2009»
15 years 11 months ago
Cheating for problem solving: a genetic algorithm with social interactions
We propose a variation of the standard genetic algorithm that incorporates social interaction between the individuals in the population. Our goal is to understand the evolutionary...
Rafael Lahoz-Beltra, Gabriela Ochoa, Uwe Aickelin

Publication
195views
14 years 2 months ago
Analog Genetic Encoding for the Evolution of Circuits and Networks
This paper describes a new kind of genetic representation called analog genetic encoding (AGE). The representation is aimed at the evolutionary synthesis and reverse engineering of...
Claudio Mattiussi, Dario Floreano
GECCO
2005
Springer
126views Optimization» more  GECCO 2005»
15 years 10 months ago
Not all linear functions are equally difficult for the compact genetic algorithm
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Stefan Droste
BMCBI
2007
152views more  BMCBI 2007»
15 years 4 months ago
Recodon: Coalescent simulation of coding DNA sequences with recombination, migration and demography
Background: Coalescent simulations have proven very useful in many population genetics studies. In order to arrive to meaningful conclusions, it is important that these simulation...
Miguel Arenas, David Posada