Disadvantages to using simple step functions for activation in neural networks?
The disadvantage would be that your fitness landscape would look less smooth (a small change in your weights may result in a big change in the output or no change at all). This may affect the convergence speed of your GA, since small changes in the chromossomes may not produce differences in fitness, rendering it blind to some benefical changes.
If your problem is performance, I'd suggest to try the hard ReLU activation function instead of a sigmoid one.