Dear Zakaria Al Ameer, Search the following titles you will get some help.

Genetic Algorithm Toolbox

Genetic and Evolutionary Algorithm Toolbox (GEATbx)

Evolutionary Algorithms for MATLAB

Genetic/Evolutionary Algorithms for MATLAB

Normally, GA is used to solve NP hard problems the final solution is the optimum one but not the decisive one. Your solution to your problem depends on what is your objective (s) what are the constraints? how do you want to represent your population? what type of reproduction operators do you want to use? do you want to give priority to exploration or exploitation?

If you know how to answer the above questions you can find a representation for your problem to be solved by GA (see my articles)

all you need is performance measure. The only link between GA and your problem is the fitness function. Once this fitness is defined the matlab toolbox will take care of the rest. However, for these problems do not expect an optimal solution. The best to expect is a suboptimal one; There results will also be more or less inconsistent. I tried a similar problem (QAP) the results were not as impressive as I wanted. You may explore PSO (partical swarm optimization). It is much simpler and more promising.

You might like to specify your problem in more detail. As it sounds right now, I would ask why to apply a genetic algorithm and why not an exact approach. The dimensions of your problem do not seem out of reach for an exact approach...

Please indicate properly what are your objectives is it only an optimal location for a facility? in other words where it is accessible easily and very fast "shortest route for all mine locations".

Define your given data is it all possible geographic locations (coordinates) of the mine facility? what are the constraints? I can suggest that the objective function can be the minimum distance from the three mines toward the facility. Please be more clear with your problem.