standardize dataset with numerical and dummy features
1) Dummy variables doesn't need to be standardized, just numerical ones, but if you use MaxMin scaler you can pass both numerical and dummy variables because this scaler doesn't change the values of dummy variables, try to apply the equation to dummy variables to see.

$$ z_i=\frac{x_i-\min(x)}{\max(x)-\min(x)} $$

2) That's a trick question and the response is: it depends. If you have some outlier in your data MaxMin doesn't fit well, because this outlier will be replaced by 0 or 1 and the rest of data will be confined in a very restricted range of values, in this case you should use a normal scaler.