Finding the parameters for model using genetic algorithm

Hi, the situation is this. I have a matlab function f1 which takes input parameters (lets call them input_par) . It then creates a file (lets call it file_due_to_matlab.txt). then calls another software. this another software uses file_due_to_matlab.txt and stores result in yet another file (lets call it file_from_soft.txt). matlab now reads file_from_soft.txt. what this file (file_from_soft.txt) has is output of model which depend on input_par! so after one iteration i want to compare this output of model and tweak the parameters to fit the experimental data. I wanted to use Genetic Algos. because they seem to be suited better when search space is large. Any pointers to right starting point would be great help. My idea is to put all the matlab stuff into a function which after all processing with another soft produces just the output. ( so that all GA sees is the output when it choose the input parameters. Is this the right way to go or do you suggest smething better.