Package org.biojavax.ga.functions
package org.biojavax.ga.functions
GA functions
A genetic algorithm requires a number of functions. This package provides the interfaces for those functions and simple implementations. By implementing, mixing and matching these functions you can create highly customized genetic algorithms.
A GA requires (in alphabetical order): a CrossOverFunction
to govern the behaivour of 'chromosome' crossovers, a FitnessFunction
to determine the fitness of each organism after each iteration, a
MutationFuntion to govern mutation behaivour, and a SelectionFunction
to select organisms for the next round of replication.
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ClassDescriptionAbstract implementation of
CrossOverFunction.Abstract implementation ofMutationFunctionall custom implementations should inherit from here.Crosses two chromosomes.A place holder CrossOverFunction that doesn't perform cross oversCalculates the fitness of anOrganismin aPopulationofOrganismsHolds the results of a CrossOver event, objects of this type are made byCrossOverFunctionsHolds the results of a CrossOver event, objects of this type are made byCrossOverFunctionsA class that mutates aSymbolListPlace Holder class that doesn't mutate its SymbolListsThis does a 2-point-crossover on two chromosomes keeping the Symbols in each chromosome constant.A Selection function that determines the proportion of individuals in a new population proportionally to their fitness.Selects Organisms for Replication and returns the offspring.Selects individuals who's fitness exceeds a threshold value.Simple Implementation of theCrossOverFunctioninterfaceSimple implementation of theGACrossinterface.Simple no frills Implementation of the MutationFunction interfaceThis class does a sort of mutation by exchanging two positions on the chromosome.Tournament Selection chooses the best organisms from n random subsets of a given population.