Package | Description |
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smile.gap |
Genetic algorithm and programming.
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Modifier and Type | Interface and Description |
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interface |
FitnessMeasure<T extends Chromosome>
A measure to evaluate the fitness of chromosomes.
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class |
GeneticAlgorithm<T extends Chromosome>
A genetic algorithm (GA) is a search heuristic that mimics the process of
natural evolution.
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Modifier and Type | Interface and Description |
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interface |
LamarckianChromosome
Artificial chromosomes used in Lamarckian algorithm that is a hybrid of
of evolutionary computation and a local improver such as hill-climbing.
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Modifier and Type | Class and Description |
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class |
BitString
The standard bit string representation of the solution domain.
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Modifier and Type | Method and Description |
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Chromosome[] |
Chromosome.crossover(Chromosome another)
Returns a pair of offsprings by crossovering this one with another one
according to the crossover rate, which determines how often will be
crossover performed.
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Chromosome |
Chromosome.newInstance()
Returns a new random instance.
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T[] |
GeneticAlgorithm.population()
Returns the population of current generation.
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Modifier and Type | Method and Description |
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int |
BitString.compareTo(Chromosome o) |
Chromosome[] |
Chromosome.crossover(Chromosome another)
Returns a pair of offsprings by crossovering this one with another one
according to the crossover rate, which determines how often will be
crossover performed.
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BitString[] |
BitString.crossover(Chromosome another) |
Constructor and Description |
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GeneticAlgorithm(T[] seeds)
Constructor.
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GeneticAlgorithm(T[] seeds,
GeneticAlgorithm.Selection selection)
Constructor.
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