Uses of Class
com.ibm.able.beans.AbleGeneticObject

Packages that use AbleGeneticObject

com.ibm.able.agents	The AGENTS package provides a set of agents extending AbleDefaultAgent which contain AbleBean components.
com.ibm.able.examples.genetic	The ABLE genetic examples....

Uses of AbleGeneticObject in com.ibm.able.agents

Methods in com.ibm.able.agents that return AbleGeneticObject

AbleGeneticObject[]	AbleGeneticSearchAgent.createChildren(java.lang.Object[] chromosome) Given a newly derived chromosome(s), create a new population member(s) and initialize it/them.
AbleGeneticObject	AbleGeneticSearchAgent.createChild(java.lang.Object chromosome) Given a prospective chromosome a) see if dups are allowed and if it is unique b) if ok, create a child genetic object from the chromsome and initialize the associated bean (if any)
AbleGeneticObject[]	AbleGeneticSearchAgent.selectParents() choose two population members to reproduce using rouletteWheel selection technique
AbleGeneticObject	AbleGeneticSearchAgent.rouletteWheelSelection() Select a member of the population using the roulette wheel algorithm

Methods in com.ibm.able.agents with parameters of type AbleGeneticObject

protected void

AbleGeneticSearchAgent.insertIntoPopulation(AbleGeneticObject newMember, java.util.Vector list) Insert a member into the population vector sorted by raw fitness update the min and max fitness values

Uses of AbleGeneticObject in com.ibm.able.examples.genetic

Subclasses of AbleGeneticObject in com.ibm.able.examples.genetic

class	TstGeneticFunction1 This class maximizes the number of on bits (1) in a binary string
class	TstGeneticFunction2 This class implements the F6 function described in the first chapter of The Handbook of Genetic Algorithms (Davis) It uses a traditional binary string representation
class	TstGeneticFunction2a This class implements the F6 function described in the first chapter of The Handbook of Genetic Algorithms (Davis) Is used a hybrid (numeric) chromosome representation
class	TstGeneticFunction3 This class shows an example of optimizing input parameters for neural networks