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Posted to issues@commons.apache.org by "AVIJIT BASAK (Jira)" <ji...@apache.org> on 2021/08/31 15:35:00 UTC
[jira] [Updated] (MATH-1619) Implementation of Adaptive Probability
Generation
[ https://issues.apache.org/jira/browse/MATH-1619?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
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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