ec.vector.breed

Class VectorCrossoverPipeline

java.lang.Object

ec.BreedingSource

ec.BreedingPipeline

ec.vector.breed.VectorCrossoverPipeline

All Implemented Interfaces:

Prototype, Setup, SteadyStateBSourceForm, RandomChoiceChooserD, Serializable, Cloneable

public class VectorCrossoverPipeline
extends BreedingPipeline

VectorCrossoverPipeline is a BreedingPipeline which implements a simple default crossover for VectorIndividuals. Normally it takes two individuals and returns two crossed-over child individuals. Optionally, it can take two individuals, cross them over, but throw away the second child (a one-child crossover). VectorCrossoverPipeline works by calling defaultCrossover(...) on the first parent individual.

Typical Number of Individuals Produced Per produce(...) call
2 * minimum typical number of individuals produced by each source, unless tossSecondParent is set, in which case it's simply the minimum typical number.

Number of Sources
2

Parameters

base.toss bool = true or false (default)/td>

(after crossing over with the first new individual, should its second sibling individual be thrown away instead of adding it to the population?)

Default Base
vector.xover

Version:

1.0

Author:

Sean Luke

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static int	NUM_SOURCES
static String	P_CROSSOVER
static String	P_TOSS
(package private) VectorIndividual[]	parents Temporary holding place for parents
boolean	tossSecondParent Should the pipeline discard the second parent after crossing over?

Fields inherited from class ec.BreedingPipeline

DYNAMIC_SOURCES, likelihood, mybase, P_LIKELIHOOD, P_NUMSOURCES, P_SOURCE, sources, V_SAME

Fields inherited from class ec.BreedingSource

NO_PROBABILITY, P_PROB, probability

Constructor Summary

Constructors

Constructor and Description
VectorCrossoverPipeline()

Method Summary

Methods

Modifier and Type	Method and Description
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 2
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 2 * minimum number of typical individuals produced by any sources, else 1* minimum number if tossSecondParent is true.

Methods inherited from class ec.BreedingPipeline

finishProducing, individualReplaced, maxChildProduction, minChildProduction, preparePipeline, prepareToProduce, produces, reproduce, sourcesAreProperForm

Methods inherited from class ec.BreedingSource

getProbability, pickRandom, setProbability, setupProbabilities

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

P_TOSS

public static final String P_TOSS

See Also:

Constant Field Values

P_CROSSOVER

public static final String P_CROSSOVER

See Also:

Constant Field Values

NUM_SOURCES

public static final int NUM_SOURCES

See Also:

Constant Field Values

tossSecondParent

public boolean tossSecondParent

Should the pipeline discard the second parent after crossing over?

parents

VectorIndividual[] parents

Temporary holding place for parents

Constructor Detail

VectorCrossoverPipeline

public VectorCrossoverPipeline()

Method Detail

defaultBase

public Parameter defaultBase()

Description copied from interface: Prototype

Returns the default base for this prototype. This should generally be implemented by building off of the static base() method on the DefaultsForm object for the prototype's package. This should be callable during setup(...).

numSources

public int numSources()

Returns 2

Specified by:

numSources in class BreedingPipeline

clone

public Object clone()

Description copied from interface: Prototype

Creates a new individual cloned from a prototype, and suitable to begin use in its own evolutionary context.

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:

• If you hold objects which are shared with other instances, don't clone them.
• If you hold objects which must be unique, clone them.
• If you hold objects which were given to you as a gesture of kindness, and aren't owned by you, you probably shouldn't clone them.
• DON'T attempt to clone: Singletons, Cliques, or Groups.
• Arrays are not cloned automatically; you may need to clone an array if you're not sharing it with other instances. Arrays have the nice feature of being copyable by calling clone() on them.

Implementations.

• If no ancestor of yours implements clone(), and you have no need to do clone deeply, and you are abstract, then you should not declare clone().
• If no ancestor of yours implements clone(), and you have no need to do clone deeply, and you are not abstract, then you should implement it as follows:

   public Object clone() 
       {
       try
           { 
           return super.clone();
           }
       catch ((CloneNotSupportedException e)
           { throw new InternalError(); } // never happens
       }
          

• If no ancestor of yours implements clone(), but you need to deep-clone some things, then you should implement it as follows:

   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;
       } 
          

• If an ancestor has implemented clone(), and you also need to deep clone some things, then you should implement it as follows:

   public Object clone() 
       { 
       MyObject myobj = (MyObject) (super.clone());
  
       // put your deep-cloning code here...
  
       return myobj;
       } 
          

Specified by:

clone in interface Prototype

Overrides:

clone in class BreedingPipeline

setup

public void setup(EvolutionState state,
         Parameter base)

Description copied from class: BreedingSource

Sets up the BreedingPipeline. You can use state.output.error here because the top-level caller promises to call exitIfErrors() after calling setup. Note that probability might get modified again by an external source if it doesn't normalize right.

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}.

Specified by:

setup in interface Prototype

Specified by:

setup in interface Setup

Overrides:

setup in class BreedingPipeline

See Also:

Prototype.setup(EvolutionState,Parameter)

typicalIndsProduced

public int typicalIndsProduced()

Returns 2 * minimum number of typical individuals produced by any sources, else 1* minimum number if tossSecondParent is true.

Overrides:

typicalIndsProduced in class BreedingPipeline

produce

public int produce(int min,
          int max,
          int start,
          int subpopulation,
          Individual[] inds,
          EvolutionState state,
          int thread)

Description copied from class: BreedingSource

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. max must be >= min, and min must be >= 1. For example, crossover might typically produce two individuals, tournament selection might typically produce a single individual, etc.

Specified by:

produce in class BreedingSource