# How to define a fitness function to make sure the best fitness value is 'close to 9' in genetic algorithm

I am learning about genetic algorithms (GA), but I encountered a question about the definition of the fitness function used in GA.

I understand that the fitness function should return a scalar value (e.g. to make sure to return the maximum value for a given individual).

For example, if one wanted to optimize a small molecule $$logP$$ (to ensure that the returned $$logP$$ has the maximum values), one can define the fitness value thusly: $$J(m) = logP$$, and then use GA to optimize the $$logP$$.

But my question is that I want to make sure that the $$logP$$ has a value close to 9 (rather than the larger the better), the more closer to 9 the better.

In this case how can I define the fitness function used in GA?

Thanks.