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https://issues.apache.org/jira/browse/MATH-1619?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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AVIJIT BASAK updated MATH-1619:
-------------------------------
Description:
An Adaptive Probability Generation has been proposed as part of the Jira. A new
class AdaptiveGeneticAlgorithm should be introduced as an implementation, which
would extend the AbstractGeneticAlgorithm class. A new ProbabilityGenerator
interface would be introduced to enable configurable probability generation
strategy. The implementation of the ProbabilityGenerator interface for
crossover and mutation probability generation will be provided during creation
of AdaptiveGeneticAlgorithm instance. There can be different probability
generation strategy like based on chromosome rank, no of generations passed
etc, population statistics\al parameters. The design of ProbabilityGenerator
should consider for arguments like chromosome rank, population stats etc. to
enable interchangeable probability generation by the same
AdaptiveGeneticalgorithm class.
Removed Components: None
New Components: AdaptiveGeneticAlgorithm, CrossoverProbabilityGenerator,
MutationProbabilityGenerator ConstantCrossoverProbabilityGenerator,
ConstantMutationProbabilityGenerator,
LinearAdaptiveCrossoverProbabilityGenerator,
LinearAdaptiveMutationProbabilityGenerator,
LinearAdaptiveRandomCrossoverProbabilityGenerator,
LinearAdaptiveRandomMutationProbabilityGenerator,
TimeVaryingLinearAdaptiveCrossoverProbabilityGenerator,
TimeVaryingLinearAdaptiveMutationProbabilityGenerator,
Affected components: None
was:
An Adaptive Probability Generation has been proposed as part of the Jira. A new
class AdaptiveGeneticAlgorithm should be introduced as an implementation, which
would extend the AbstractGeneticAlgorithm class. A new ProbabilityGenerator
interface would be introduced to enable configurable probability generation
strategy. The implementation of the ProbabilityGenerator interface for
crossover and mutation probability generation will be provided during creation
of AdaptiveGeneticAlgorithm instance. There can be different probability
generation strategy like based on chromosome rank, no of generations passed
etc, population statistics\al parameters. The design of ProbabilityGenerator
should consider for arguments like chromosome rank, population stats etc. to
enable interchangeable probability generation by the same
AdaptiveGeneticalgorithm class.
Removed Components: None
New Components: AdaptiveGeneticAlgorithm, ProbabilityGenerator,
ConstantProbabilityGenerator, LinearAdaptiveProbabilityGenerator,
TimeVaryingLinearAdaptiveProbabilityGenerator
Affected components: None
> Implementation of Adaptive Probability Generation
> -------------------------------------------------
>
> Key: MATH-1619
> URL: https://issues.apache.org/jira/browse/MATH-1619
> Project: Commons Math
> Issue Type: Sub-task
> Affects Versions: 3.6.1
> Reporter: AVIJIT BASAK
> Priority: Major
>
> An Adaptive Probability Generation has been proposed as part of the Jira. A
> new class AdaptiveGeneticAlgorithm should be introduced as an implementation,
> which would extend the AbstractGeneticAlgorithm class. A new
> ProbabilityGenerator interface would be introduced to enable configurable
> probability generation strategy. The implementation of the
> ProbabilityGenerator interface for crossover and mutation probability
> generation will be provided during creation of AdaptiveGeneticAlgorithm
> instance. There can be different probability generation strategy like based
> on chromosome rank, no of generations passed etc, population statistics\al
> parameters. The design of ProbabilityGenerator should consider for arguments
> like chromosome rank, population stats etc. to enable interchangeable
> probability generation by the same AdaptiveGeneticalgorithm class.
> Removed Components: None
> New Components: AdaptiveGeneticAlgorithm, CrossoverProbabilityGenerator,
> MutationProbabilityGenerator ConstantCrossoverProbabilityGenerator,
> ConstantMutationProbabilityGenerator,
> LinearAdaptiveCrossoverProbabilityGenerator,
> LinearAdaptiveMutationProbabilityGenerator,
> LinearAdaptiveRandomCrossoverProbabilityGenerator,
> LinearAdaptiveRandomMutationProbabilityGenerator,
> TimeVaryingLinearAdaptiveCrossoverProbabilityGenerator,
> TimeVaryingLinearAdaptiveMutationProbabilityGenerator,
> Affected components: None
>
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