Why does my genetic algorithm optimization programming converge early?

Hello:)

I'd like to find the optimal solution for my object function.

But the programming always converge earlier than I expected.

Like this:

The obejctive function code is:

M=[39058 41131 33961 31946 21925 18730 15934 14114 15101 28402 28412 30202 29819 29096 27838 25857 23531 18800 27003 26058 24941 23078 11337 10134 9933 9161];

S=[a b c d e f g h i j k l m n o p q r s t u v w x y z];

N=5.356795e16*S;

F=(M-N)*(M-N)';

and the values of matrix S are read from txt file.

Number of variables is 121, population size is 200, elite count is 2, crossover fraction is 0.8, function tolerance is 1e-6, constraint tolerance is 1e-3.

I hope the optimization process can converge until fitness value=0, should I change the obejective function or change any options?

Thanks for asking my question:)