Why should I change the mutation function to '@mutationadaptfeasile' when using lower and upper bounds?
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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
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.
Hope this helps!
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