public class MultipleVectorCrossoverPipeline extends BreedingPipeline
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
Modifier and Type | Field and Description |
---|---|
static java.lang.String |
P_CROSSOVER
default base
|
DYNAMIC_SOURCES, likelihood, mybase, P_LIKELIHOOD, P_NUMSOURCES, P_SOURCE, sources, V_SAME, V_STUB
NO_PROBABILITY, P_PROB, probability
Constructor and Description |
---|
MultipleVectorCrossoverPipeline() |
Modifier and Type | Method and Description |
---|---|
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 |
numSources()
Returns the number of parents
|
int |
produce(int min,
int max,
int subpopulation,
java.util.ArrayList<Individual> inds,
EvolutionState state,
int thread,
java.util.HashMap<java.lang.String,java.lang.Object> misc)
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
|
fillStubs, finishProducing, individualReplaced, maxChildProduction, minChildProduction, preparePipeline, prepareToProduce, produces, sourcesAreProperForm
getProbability, pickRandom, setProbability, setupProbabilities
public static final java.lang.String P_CROSSOVER
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 subpopulation, java.util.ArrayList<Individual> inds, EvolutionState state, int thread, java.util.HashMap<java.lang.String,java.lang.Object> misc)
BreedingSource
produce
in class BreedingSource