max - Are all genetic algorithms maximization algorithms? -


I'm not sure that my understanding of maximization and minimizing is correct.

Some functions F (X, Y, Z) I have to find out what the maximum value will be, which is maximum, right? And if I want to get the least value which is least?

So if a genetic algorithm is a search algorithm trying to maximize some fitness function, then what is the definition of maximization algorithms?

then ask for some function F (X, Y, Z), let me know this Is to determine whether the highest value is the maximum, right? And if I want to get the lowest price which is least?

Yes, that definition is correct.

So if a genetic algorithm is a search, the algorithm is trying to maximize some fitness functions, can they be maximizing algorithms by definition?

Too much yes, although I'm not sure that "Maximization Algorithm" is a well-used word, and only if a genetic algorithm is defined, which I believe It's not that it's strictly.

The generic algorithm can also try some target function values ​​to reduce the distance, or reduce the function value, but again, it is again recycled as maximization without loss of normality. Can be reserved.

Perhaps more importantly even a function is not strictly required - the candidates need to be comparable. If they have, it is possible to resume it as a maximum compensation problem. If they do not have the total order, then it can be a bit difficult for the candidates to get fairly better than all other people, although there is nothing to stop you from running GA on this type of data. Finally, trying to maximize a function is ideal (and possibly how you will define it), but do not be surprised if you do not do GA that do not.

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