Which is a better method Lasso regression or sequential Foward selection?
I think there is no obvious advantage of one algorithm over another: I'd suggest running cross-validation to investigate which works best for the data at hand. You've suggested forward stepwise and Lasso, which both performs feature selection, you could also investigate backward stepwise and best-subset selection. Linear regression models are fast to train, so maybe you could investigate the cross-validation error for all 4 algorithms.

Hope this helps.