why the penalty of ga, when all the population violates the nonlinear constraints, is smaller than the penalty of feasible populations?
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I have integer problem with nonlinear constraints. So, at the beggining there are only few integer options (the problem's boundary increases through time) and sometimes all the populations my violate the non-linear constraint. For example, the penalityt value of the first generation with feasible population is 5, then ga assignes penality value 1 when the entire population in the second generation violates the non-linear constraint.
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Jasvin
le 21 Sep 2023
Hi Emebet,
So, this is a problem that exists with all optimization algorithms in MATLAB. The following MATLAB Answers post would help you gain more insight into what is happening and provide helpful links:
Hope this helps!
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