Searches for the optimal values of k and d for a given time series. First, values corresponding to instants from initial + 1 to the last one are predicted. The first value predicted, which corresponds to instant initial + 1, is calculated using instants from 1 to instant initial; the second value predicted, which corresponds to instant initial + 2, is predicted using instants from 1 to instant initial + 1; and so on until last value, which corresponds to instant n (length of the given time series), is predicted using instants from 1 to instant n - 1. Finally, the error is evaluated between the predicted values and the real values of the series. This version of the optimization function uses a parallelized distances calculation function, and the computation of the predicted values is done parallelizing by the number of d's.