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Genetic algorithms and evolution

Journal of Theoretical Biology, 1990
The genetic algorithm (GA) as developed by Holland (1975, Adaptation in Natural and Artificial Systems. Ann Arbor: University of Michigan Press) is an optimization technique based on natural selection. We use a modified version of this technique to investigate which aspects of natural selection make it an efficient search procedure.
B H, Sumida   +3 more
openaire   +2 more sources

The compact genetic algorithm

1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360), 1999
Introduces the compact genetic algorithm (cGA) which represents the population as a probability distribution over the set of solutions and is operationally equivalent to the order-one behavior of the simple GA with uniform crossover. It processes each gene independently and requires less memory than the simple GA.
Georges R. Harik   +2 more
openaire   +1 more source

On genetic algorithms

Proceedings of the eighth annual conference on Computational learning theory - COLT '95, 1995
Eric B. Baum, Dan Boneh, Charles Garrett
openaire   +1 more source

Normalization in Genetic Algorithms

2003
Normalization is an approach that transforms the genotype of one parent to be consistent with that of the other parent. It is a method for alleviating difficulties caused by redundant encodings in genetic algorithms. We show that normalization plays a role of reducing the search space to another one of less size.
Sung-Soon Choi, Byung Ro Moon
openaire   +1 more source

Parallel Genetic Algorithms

ACM Computing Surveys, 2021
Tomohiro Harada, Enrique Alba
exaly  

Genetic algorithms

ACM Computing Surveys, 1996
openaire   +1 more source

Genetic testing in prostate cancer management: Considerations informing primary care

Ca-A Cancer Journal for Clinicians, 2022
Mary-Ellen Taplin   +2 more
exaly  

Genetic Algorithms Genetic Algorithms Agenda

2019
Ruaa Al-Falluji, Al-Zoghabi, Adel
openaire   +1 more source

Genetic algorithms for optimisation of chemical kinetics reaction mechanisms

Progress in Energy and Combustion Science, 2004
Mohamed Pourkashanian   +2 more
exaly  

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