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

["AVIJIT BASAK (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/MATH-1563?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17368095#comment-17368095 ] 

AVIJIT BASAK commented on MATH-1563:
------------------------------------

Hi

         Thanks for this reply. I did not notice this assuming the proposal
has been rejected. Kindly allow me some time. I shall do the necessary
changes and get back to you.

Thanks & Regards
--Avijit Basak

On Sat, 29 May 2021 at 18:05, Gilles Sadowski (Jira) <ji...@apache.org>



-- 
Avijit Basak


> 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
>            Priority: Major
>
> 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.



--
This message was sent by Atlassian Jira
(v8.3.4#803005)