  A new method is introduced to create artificial time sequences that fulfil
given constraints but are random otherwise. Constraints are usually derived
from a measured signal for which surrogate data are to be generated. They are
fulfilled by minimizing a suitable cost function using simulated annealing. A
wide variety of structures can be imposed on the surrogate series, including
multivariate, nonlinear, and nonstationary properties. When the linear
correlation structure is to be preserved, the new approach avoids certain
artifacts generated by Fourier-based randomization schemes.
