Crossover (genetic algorithm)

Known as: Crossover, Recombination (genetic algorithm) 
In genetic algorithms, crossover is a genetic operator used to vary the programming of a chromosome or chromosomes from one generation to the next… (More)
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Highly Cited
2008
Highly Cited
2008
Parent-centric real-parameter crossover operators create the offspring in the neighbourhood of one of the parents, the female… (More)
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Highly Cited
2007
Highly Cited
2007
Research into adjusting the probabilities of crossover and mutation pm in genetic algorithms (GAs) is one of the most significant… (More)
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Highly Cited
2004
Highly Cited
2004
An evolutionary recurrent network which automates the design of recurrent neural/fuzzy networks using a new evolutionary learning… (More)
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Highly Cited
2003
Highly Cited
2003
The main real-coded genetic algorithm (RCGA) research effort has been spent on developing efficient crossover operators. This… (More)
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Highly Cited
1999
Highly Cited
1999
This paper introduces the compact genetic algorithm (cGA) which represents the population as a probability distribution over the… (More)
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Highly Cited
1998
Highly Cited
1998
In this paper, we propose a hybrid algorithm for finding a set of nondominated solutions of a multi-objective optimization… (More)
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Highly Cited
1998
Highly Cited
1998
Genetic Algorithms The basic principles of Genetic Algorithm (GA) were first proposed by Holland [4]. It is inspired by the… (More)
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Highly Cited
1997
Highly Cited
1997
Genetic algorithms are adaptive methods which may be used to solve search and optimization problems. Genetic algorithms process a… (More)
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Highly Cited
1992
Highly Cited
1992
On the basis of early theoretical and empirical studies, genetic algorithms have typically used 1 and 2-point crossover operators… (More)
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Highly Cited
1990
Highly Cited
1990
In this paper we present some theoretical and empirical results on the interacting roles of population size and crossover in… (More)
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