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Abstract: In this paper a new genetic algorithm called the Breeder Genetic Algorithm (BGA) is introduced. The BGA is based on artificial selection similar to that used by human breeders. A predictive model for the BGA is presented which is derived from quantitative genetics. The model is used to predict the behavior of the BGA for simple test functions. Different mutation schemes are compared by computing the expected progress to the solution. (Update)
Context of citations to this paper: More
...making) 18] See [19] for more details. The core of the genetic algorithm we have used is based on the Breeder Genetic Algorithm [20]. It utilises genetic operators suitable for real valued chromosomes (arithmetic crossover, exponential mutation etc. and is adapted to...
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BibTeX entry: (Update)
Heinz Mtihlenbein and Dirk Schlierkamp-Voosen. Predictive models for the breeder genetic algorithm I: Continuous parameter optimization. Evolutionary Computations, 1(1):2549, 1993. http://citeseer.ist.psu.edu/mtihlenbein93predictive.html More
@misc{ mtihlenbein93predictive,
author = "H. Mtihlenbein and D. Schlierkamp-Voosen",
title = "Predictive models for the breeder genetic algorithm I: Continuous parameter
optimization",
text = "Heinz Mtihlenbein and Dirk Schlierkamp-Voosen. Predictive models for the
breeder genetic algorithm I: Continuous parameter optimization. Evolutionary
Computations, 1(1):2549, 1993.",
year = "1993",
url = "citeseer.ist.psu.edu/mtihlenbein93predictive.html" }
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