I am trying to implement a fitness function for a genetic algorithm and have problem with understanding what function maximization means. In the paper which I use as the basis of the algorithm, the fitness function is defined as (1-RC) + (1-RO), where RC and RO are floating point values between 0 and 1, which I calculate using another formulas. However in the next paragraph of the article it is written - "This function (fitness function) has to be maximized"I am struggling to understand what that means. Could you please explain it in easy-to-understand way for a Math noob? Thank you!

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I am trying to implement a fitness function for a genetic algorithm and have problem with understanding what function maximization means. In the paper which I use as the basis of the algorithm, the fitness function is defined as (1-RC) + (1-RO), where RC and RO are floating point values between 0 and 1, which I calculate using another formulas. However in the next paragraph of the article it is written - &quot;This function (fitness function) has to be maximized&quot;I am struggling to understand what that means. Could you please explain it in easy-to-understand way for a Math noob? Thank you!

livin4him777lf · Accepted Answer

Alright, thank you, I think I get it now. This is the whole purpose of the fitness function in evolutionary programming, to evolve the most suitable individual with parameters which will cause the fitness function to reach maximum value. I thought there is something more to this, math-related which I don&#039;t understand. Thanks!

I am trying to implement a fitness function for a genetic algorithm and have problem with understand

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