[TASK] Enabling adaptive mutation and crossover in Genetic Algorithm

[Jimmy-INL]

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Issue Description

Is your feature request related to a problem? Please describe.
Currently the Genetic Algorithms optimizers assumes constant crossover and mutation probabilities, it would be extremely benificial if we added the capability of adaptively changing these probabilities through iterations, this will assure diversity at the beginning and allow to explore the search space, but then once the optimizer made a good progress these probabilities should change.

Describe the solution you'd like
Either a new submode in the xml or a new abstracted function is added to compute the probability at each iteration.

Describe alternatives you've considered
N/A

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For Change Control Board: Issue Review

This review should occur before any development is performed as a response to this issue.

• 1. Is it tagged with a type: defect or task?
• 2. Is it tagged with a priority: critical, normal or minor?
• 3. If it will impact requirements or requirements tests, is it tagged with requirements?
• 4. If it is a defect, can it cause wrong results for users? If so an email needs to be sent to the users.
• 5. Is a rationale provided? (Such as explaining why the improvement is needed or why current code is wrong.)

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For Change Control Board: Issue Closure

This review should occur when the issue is imminently going to be closed.

• 1. If the issue is a defect, is the defect fixed?
• 2. If the issue is a defect, is the defect tested for in the regression test system? (If not explain why not.)
• 3. If the issue can impact users, has an email to the users group been written (the email should specify if the defect impacts stable or master)?
• 4. If the issue is a defect, does it impact the latest release branch? If yes, is there any issue tagged with release (create if needed)?
• 5. If the issue is being closed without a pull request, has an explanation of why it is being closed been provided?