Why should I change the mutation function to '@mutationadaptfeasile' when using lower and upper bounds?

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lennse
lennse 2017-7-26
回答： Saurabh Gupta 2017-7-31
Many MathWorks examples about the genetic algorithm use constraints, including lower and upper bounds. When they call the algorithm and demonstrate the result, nothing is said about using a nondefault mutation function. Why do they not worry about this warning I'm getting?

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Saurabh Gupta
Saurabh Gupta 2017-7-31
The following documentation explains that "default mutation function, mutationgaussian, is only appropriate for unconstrained minimization problems", so mutation function mutationadaptfeasible is required for constrained minimization problems.
https://www.mathworks.com/help/releases/R2017a/gads/examples/constrained-minimization-using-the-genetic-algorithm.html?searchHighlight=mutationadaptfeasible&s_tid=doc_srchtitle#zmw57dd0e2113
Hope this helps!

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