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java.lang.Objectec.BreedingSource
ec.BreedingPipeline
ec.vector.breed.MultipleVectorCrossoverPipeline
public class MultipleVectorCrossoverPipeline
MultipleVectorCrossoverPipeline is a BreedingPipeline which implements a uniform (any point) crossover between multiple vectors. It is intended to be used with three or more vectors. It takes n parent individuals and returns n crossed over individuals. The number of parents and consequently children is specified by the number of sources parameter.
The standard vector crossover probability is used for this crossover type.
Note : It is necessary to set the crossover-type parameter to 'any'
in order to use this pipeline.
Typical Number of Individuals Produced Per produce(...) call
number of parents
Number of Sources
variable (generally 3 or more)
Default Base
vector.multixover
Field Summary | |
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static java.lang.String |
P_CROSSOVER
default base |
Fields inherited from class ec.BreedingPipeline |
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DYNAMIC_SOURCES, mybase, P_NUMSOURCES, P_SOURCE, sources, V_SAME |
Fields inherited from class ec.BreedingSource |
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CHECKBOUNDARY, DEFAULT_PRODUCED, NO_PROBABILITY, P_PROB, probability, UNUSED |
Constructor Summary | |
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MultipleVectorCrossoverPipeline()
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Method Summary | |
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java.lang.Object |
clone()
Creates a new individual cloned from a prototype, and suitable to begin use in its own evolutionary context. |
Parameter |
defaultBase()
Returns the default base for this prototype. |
int |
multipleBitVectorCrossover(int min,
int max,
int start,
int subpopulation,
Individual[] inds,
EvolutionState state,
int thread)
Crosses over the Bit Vector Individuals using a uniform crossover method. |
int |
multipleByteVectorCrossover(int min,
int max,
int start,
int subpopulation,
Individual[] inds,
EvolutionState state,
int thread)
Crosses over the Byte Vector Individuals using a uniform crossover method. |
int |
multipleDoubleVectorCrossover(int min,
int max,
int start,
int subpopulation,
Individual[] inds,
EvolutionState state,
int thread)
Crosses over the Double Vector Individuals using a uniform crossover method. |
int |
multipleFloatVectorCrossover(int min,
int max,
int start,
int subpopulation,
Individual[] inds,
EvolutionState state,
int thread)
Crosses over the Float Vector Individuals using a uniform crossover method. |
int |
multipleGeneVectorCrossover(int min,
int max,
int start,
int subpopulation,
Individual[] inds,
EvolutionState state,
int thread)
Crosses over the Gene Vector Individuals using a uniform crossover method. |
int |
multipleIntegerVectorCrossover(int min,
int max,
int start,
int subpopulation,
Individual[] inds,
EvolutionState state,
int thread)
Crosses over the Integer Vector Individuals using a uniform crossover method. |
int |
multipleLongVectorCrossover(int min,
int max,
int start,
int subpopulation,
Individual[] inds,
EvolutionState state,
int thread)
Crosses over the Long Vector Individuals using a uniform crossover method. |
int |
multipleShortVectorCrossover(int min,
int max,
int start,
int subpopulation,
Individual[] inds,
EvolutionState state,
int thread)
Crosses over the Short Vector Individuals using a uniform crossover method. |
int |
numSources()
Returns the number of parents |
int |
produce(int min,
int max,
int start,
int subpopulation,
Individual[] inds,
EvolutionState state,
int thread)
Produces n individuals from the given subpopulation and puts them into inds[start...start+n-1], where n = Min(Max(q,min),max), where q is the "typical" number of individuals the BreedingSource produces in one shot, and returns n. |
void |
setup(EvolutionState state,
Parameter base)
Sets up the BreedingPipeline. |
int |
typicalIndsProduced()
Returns the minimum number of children that are produced per crossover |
Methods inherited from class ec.BreedingPipeline |
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finishProducing, individualReplaced, maxChildProduction, minChildProduction, preparePipeline, prepareToProduce, produces, sourcesAreProperForm |
Methods inherited from class ec.BreedingSource |
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getProbability, pickRandom, setProbability, setupProbabilities |
Methods inherited from class java.lang.Object |
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equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
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public static final java.lang.String P_CROSSOVER
Constructor Detail |
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public MultipleVectorCrossoverPipeline()
Method Detail |
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public Parameter defaultBase()
Prototype
public int numSources()
numSources
in class BreedingPipeline
public java.lang.Object clone()
Prototype
Typically this should be a full "deep" clone. However, you may share certain elements with other objects rather than clone hem, depending on the situation:
Implementations.
public Object clone()
{
try
{
return super.clone();
}
catch ((CloneNotSupportedException e)
{ throw new InternalError(); } // never happens
}
public Object clone()
{
try
{
MyObject myobj = (MyObject) (super.clone());
// put your deep-cloning code here...
}
catch ((CloneNotSupportedException e)
{ throw new InternalError(); } // never happens
return myobj;
}
public Object clone()
{
MyObject myobj = (MyObject) (super.clone());
// put your deep-cloning code here...
return myobj;
}
clone
in interface Prototype
clone
in class BreedingPipeline
public void setup(EvolutionState state, Parameter base)
BreedingSource
The most common modification is to normalize it with some other set of probabilities, then set all of them up in increasing summation; this allows the use of the fast static BreedingSource-picking utility method, BreedingSource.pickRandom(...). In order to use this method, for example, if four breeding source probabilities are {0.3, 0.2, 0.1, 0.4}, then they should get normalized and summed by the outside owners as: {0.3, 0.5, 0.6, 1.0}.
setup
in interface Prototype
setup
in interface Setup
setup
in class BreedingPipeline
Prototype.setup(EvolutionState,Parameter)
public int typicalIndsProduced()
typicalIndsProduced
in class BreedingPipeline
public int produce(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread)
BreedingSource
produce
in class BreedingSource
public int multipleBitVectorCrossover(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread)
public int multipleByteVectorCrossover(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread)
public int multipleDoubleVectorCrossover(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread)
public int multipleFloatVectorCrossover(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread)
public int multipleGeneVectorCrossover(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread)
public int multipleIntegerVectorCrossover(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread)
public int multipleLongVectorCrossover(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread)
public int multipleShortVectorCrossover(int min, int max, int start, int subpopulation, Individual[] inds, EvolutionState state, int thread)
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