To avoid exhaustive enumeration, Daulton et al. proposed a probabilistic reparameterization (PR) approach. In this method, discrete variables are sampled from a probability distribution that is parameterized by continuous variables. This allows for more efficient optimization of mixed-variable problems by optimizing over the continuous reparameterization rather than the discrete space directly.