Details
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Improvement
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Status: Open
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Major
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Resolution: Unresolved
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Description
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.
Attachments
Attachments
Issue Links
1.
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Change in Existing Design |
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Open | Unassigned |
2.
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Implementation of Adaptive Probability Generation |
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Open | Unassigned |
3.
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Improvement of data structure for Binary Chromosome |
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Open | Unassigned |
4.
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Implementation of multi-threading in Genetic Algorithm and parallel GA with multiple populations. |
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Open | Unassigned |