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

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?

Answer 1

[Saurabh Gupta]

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!