Genetic algorithm optimization using toolbox

I want to optimize vector of complex coefficient (Contains negative values),

but I wonder how can i chose the right tools .

I proposed this tools :

Population representation and initialization : l used '' crtrp '' (given size of random real-values),

Fitness function : because i have a negative value i excluded use ''scaling'' method

( is not recommended when fitness functions produce negative results) ,so i used ''ranking''method,

Selection functions: I am confused Which methods are suitable(reins, rws, select, sus),

Crossover operators: i suggest ''recint'' method (because to support real-valued chromosome representations),

Mutation operators: i suggest 'mutbga' (real-value is available),

Could you please provide your opinion regarding this steps? If the steps are correct,

what condition should the objective function have to fit with these steps?

or is available with any objective function?