Neural Network weight selection using Genetic Algorithm
Your understanding is correct.


Yes, you do create a new neural network for each chromosome (although you're considering the network structure as fixed, so technically you could reuse them by just resetting the weights anew for each chromosome.
For the error, you're on the right track. For a GA, generally only relative differences in fitness are important, so it doesn't really matter if you divide by 100 or not -- that's just linearly scaling the fitness values. That might matter for some choices of genetic operators (e.g., roulette-wheel selection can be sensitive to absolute fitness values), but often it won't matter at all.