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Posted to issues@commons.apache.org by "AVIJIT BASAK (Jira)" <ji...@apache.org> on 2020/12/06 05:19:00 UTC

[jira] [Created] (MATH-1563) Implementation of Adaptive Probability Generation Strategy for Genetic Algorithm

AVIJIT BASAK created MATH-1563:
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             Summary: Implementation of Adaptive Probability Generation Strategy for Genetic Algorithm
                 Key: MATH-1563
                 URL: https://issues.apache.org/jira/browse/MATH-1563
             Project: Commons Math
          Issue Type: Improvement
            Reporter: AVIJIT BASAK


In Genetic Algorithm probability of crossover and mutation operation can be generated in an adaptive manner. Some experiment was done related to this and published in this article "https://www.ijcaonline.org/archives/volume175/number10/basak-2020-ijca-920572.pdf".

Currently Apache's API works on constant probability strategy. I would like to propose incorporation of rank based adaptive probability generation strategy as described in the mentioned article. This will improve the performance and robustness of the algorithm and would make this more suitable for use in higher dimensional problems like machine learning or deep learning.



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