Uses of Class
es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation.MutationOperator

Packages that use MutationOperator
es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation   
es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation.de   
es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation.real_code   
 

Uses of MutationOperator in es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation
 

Subclasses of MutationOperator in es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation
 class DoubleRandomMutation
          This class implements a double random mutation operator.
 class EvolutionaryStrategyMutation
          This class implements a mutation operator to be used with the Evoluationary Strategies.
 class GaussianMutation
          This class implements a gaussian mutation operator.
 class MOPMutation
           
 class SwapMutation
          This class implements a swap mutation operator.
 

Fields in es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation declared as MutationOperator
private  MutationOperator EvolutionaryStrategyMutation.operator
           
 

Methods in es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation that return MutationOperator
 MutationOperator EvolutionaryStrategyMutation.getOperator()
           
 

Uses of MutationOperator in es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation.de
 

Subclasses of MutationOperator in es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation.de
 class DEMutationOperator
          For each target vector xi,G, i = 1,2,...
 

Uses of MutationOperator in es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation.real_code
 

Subclasses of MutationOperator in es.udc.gii.common.eaf.algorithm.operator.reproduction.mutation.real_code
 class MichalewiczNonUniformMutation
          If this operator is applied in a generation t and gmax is the maximum number of generations then c'i= ci+&delta(t,bi-ci) if &tau = 0 ci-&delta(t,ci-ai) if &tau = 1 with &tau being a random number which may have a value of zero or one, and: &delta(t,y)=y(1-r(1-t/gmax)b) Where r is a random number from the interval [0,1] and b is a parameter chosen by the user, which determines the degree of dependency on the number of iterations.