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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Topic mentions per year

1936-2017
05010015019362016

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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
1995
Highly Cited
1995
One of the issues in evolutionary algorithms (EAs) is the relative importance of two search operators: mutation and crossover… (More)
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Highly Cited
1994
Highly Cited
1994
In this paper we describe an efficient approach for solving the economic dispatch problem using Genetic Algorithms (GAs). We… (More)
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Highly Cited
1994
Highly Cited
1994
John Holland's pioneering book Adaptation in Natural and Artificial Systems [1975, 1992] showed how the evolutionary process can… (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
1992
Highly Cited
1992
Genetic algorithms rely on two genetic operators crossover and mutation. Although there exists a large body of conventional… (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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